{"id":2154,"date":"2025-10-31T01:15:05","date_gmt":"2025-10-30T17:15:05","guid":{"rendered":"https:\/\/qtml2025.cqt.sg\/?page_id=2154"},"modified":"2025-11-14T15:24:54","modified_gmt":"2025-11-14T07:24:54","slug":"poster-sessions","status":"publish","type":"page","link":"https:\/\/qtml2025.cqt.sg\/poster-sessions\/","title":{"rendered":"Poster Sessions"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"2154\" class=\"elementor elementor-2154\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1a03989 e-flex e-con-boxed e-con e-parent\" data-id=\"1a03989\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-13ab188 e-con-full e-flex e-con e-child\" data-id=\"13ab188\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4fdf64b elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"4fdf64b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Poster Sessions<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-299e403 e-flex e-con-boxed e-con e-parent\" data-id=\"299e403\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6430294 elementor-widget elementor-widget-spacer\" data-id=\"6430294\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-53ad36b e-flex e-con-boxed e-con e-parent\" data-id=\"53ad36b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-5bef5fa e-flex e-con-boxed e-con e-parent\" data-id=\"5bef5fa\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-90fb71c elementor-widget elementor-widget-heading\" data-id=\"90fb71c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Preparing your poster<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-de86869 elementor-widget elementor-widget-text-editor\" data-id=\"de86869\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li style=\"list-style-type: none;\"><ul><li>All posters should be based on the submitted abstract that has been accepted by the Programme Committee.<\/li><li>Poster displays are limited to one side of a poster panel, 100cm (width) x 225cm tall from the floor.<\/li><li>The recommended poster size is A0 (portrait layout): 84.1cm (width) x 118.9 cm (height).<\/li><li>Be sure to include the title of the abstract, the names of the author and co-authors, and the affiliations.<\/li><li>Please note that all posters must be displayed in English.<\/li><li>It is recommended that you hand-carry your poster to the conference in a tube or portfolio case. Costs associated with the creation and shipping of the poster display are the responsibility of the authors. Poster printing will <b style=\"font-style: inherit;\">NOT<\/b><span style=\"font-size: 16px;\"> be available <\/span>on site.<\/li><li>For first-time presenters, guides on preparing impactful poster are abundant online, and you can find some inspiration <a href=\"https:\/\/www.youtube.com\/watch?v=1RwJbhkCA58\">here.<\/a> The most important feature of effective posters is that they do not contain a lot of text; good posters usually have 100-1000 words.<\/li><\/ul><\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-c34eef1 e-flex e-con-boxed e-con e-parent\" data-id=\"c34eef1\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-601d85f elementor-widget elementor-widget-spacer\" data-id=\"601d85f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-989cfb2 e-flex e-con-boxed e-con e-parent\" data-id=\"989cfb2\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-065e8cd elementor-widget elementor-widget-heading\" data-id=\"065e8cd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Displaying your poster<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-21b3405 elementor-widget elementor-widget-text-editor\" data-id=\"21b3405\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>The poster session is located next to the conference room.<\/li><li>Posters are randomly assigned to session I or II. Please check the lists below to find out which session you are presenting in.<\/li><li>Posters can be set up from 12:30 on the day of your session. Poster sessions are 16:30-18:00. Please be at your poster during this period. Posters should be removed after 18:00.<\/li><li>There is no allocated space for each poster. Please put up your printed poster on any available poster boards, first come first served.<\/li><li><b>Velcro<\/b> will be provided on site. No glue, double-sided tape, tacks or staples are permitted on the poster boards.<\/li><li>Please note that the Organising Committee is not responsible for any damage or loss of posters. Any posters remaining after the removal time will be removed and discarded after the event.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-3a9c6ab e-flex e-con-boxed e-con e-parent\" data-id=\"3a9c6ab\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c1abcad elementor-widget elementor-widget-spacer\" data-id=\"c1abcad\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-574a2ea e-flex e-con-boxed e-con e-parent\" data-id=\"574a2ea\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a952b94 elementor-widget elementor-widget-menu-anchor\" data-id=\"a952b94\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"PostersI\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5e7de24 elementor-widget elementor-widget-heading\" data-id=\"5e7de24\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Poster Session I: Monday<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5faed0c elementor-widget elementor-widget-wp-widget-custom_html\" data-id=\"5faed0c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"wp-widget-custom_html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"textwidget custom-html-widget\"><table style=\"width:100%\" border=\"2\">\r\n  <tr>\r\n    <th style=\"background-color: #1F1B55;text-align: left;color:white\">EasyChairID<\/th>\r\n<th style=\"background-color: #1F1B55;text-align: left;color: white\">Authors<\/th> \r\n    <th style=\"background-color: #1F1B55;text-align: left;color: white\">Title<\/th> \r\n  \r\n  <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t181\t<\/td>\r\n\r\n    <td>Marco Sciorilli, Lucas Borges, Giancarlo Camilo, Thiago O.\r\nMaciel, Askery Canabarro and Leandro Aolita\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA competitive NISQ and qubit-efficient solver for the LABS\r\nproblem\t<\/b><\/td> <\/tr>\r\n\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t111\t<\/td>\r\n<td>Tim Forrer, Matthew Wilson, Philip Taranto, Jisho Miyazaki\r\nand Mio Murao\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA compositional framework for leveraging quantum learning\r\nto circumvent no-go theorems\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t261\t<\/td>\r\n\r\n<td>Ian Joel David, Ilya Sinayskiy and Francesco Petruccione\r\n\r\n<\/td>\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA faster converging qDRIFT algorithm with application to\r\nHamiltonian data encoding\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t321\t<\/td>\r\n<td>Kieran McDowall, Theodoros Kapourniotis, Christopher\r\nOliver, Phalgun Lolur and Konstantinos Georgopoulos\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA Practical Cross-Platform, Multi-Algorithm Study of\r\nQuantum Optimisation for Configurational Analysis of\r\nMaterials\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t88\t<\/td>\r\n<td>Tara Kit, Leanghok Hour, Muyleang Ing and Youngsun Han\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA Resource-Efficient Quantum-Classical Model for\r\nProtein\u2013Ligand Binding Affinity Prediction\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t291\t<\/td>\r\n<td>Vincenzo Lipardi, Domenica Dibenedetto, Georgios Stamoulis\r\nand Mark H.M. Winands\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA Study on Stabilizer R\\'enyi Entropy Estimation using\r\nMachine Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t108\t<\/td>\r\n<td>Rundi Lu, Ruiqi Zhang, Weikang Li, Dong-Ling Deng and\r\nZhengwei Liu\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA Unified Frequency Principle for Quantum and Classical\r\nMachine Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t33\t<\/td>\r\n<td>Mafalda Ram\u00f4a\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tADAPT-VQE with Operator Removal\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t11\t<\/td>\r\n<td>Mandadi Sindhu, M.Mohan Sai Reddy and Devireddy Sai\r\nSanthosh Reddy\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAdvanced Ensemble Smart Classifications for Nifty Smart\r\nMarket Trends\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t298\t<\/td>\r\n<td>Xinbiao Wang, Yuxuan Du, Zihan Lou, Yang Qian, Kaining\r\nZhang, Yong Luo, Bo Du and Dacheng Tao\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAiDE-Q: Synthetic Labeled Datasets Can Enhance Learning\r\nModels for Quantum Property Estimation\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t4\t<\/td>\r\n<td>Matthew Ho, Jun Yong Khoo, Adrian Mak and Stefano Carrazza\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAI-Powered Noisy Quantum Emulation: Generalized Gate-Based\r\nProtocols for Hardware-Agnostic Simulation\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t148\t<\/td>\r\n<td>Li Xin and Zhang-Qi Yin\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAn Attention-Based Quantum Phase Transition Detection on\r\nNISQ Devices\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t42\t<\/td>\r\n<td>Yuqi Huang, Vincent Y. F. Tan and Sharu Jose\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tBalancing Expressivity and Learnability in Quantum Kernel\r\nBandit Optimization\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t331\t<\/td>\r\n<td>Laura Henderson, Kerstin Beer, Salini Karuvade, Riddhi\r\nGupta and Angela White\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tBarren plateau-free and noise-robust quantum advantage for\r\nlearning data with group symmetries\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t126\t<\/td>\r\n<td>Alexandra Ram\u00f4a, Raffaele Santagati and Nathan Wiebe\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tBayesian Learning of Quantum Hardware Dynamics\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t192\t<\/td>\r\n<td>Dominic Lowe, Myungshik Kim and Roberto Bondesan\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tBenchmarking Quantum Algorithms for Gaussian Process\r\nRegression\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t334\t<\/td>\r\n<td>Charitha Pathipati, Tirupati Bolisetti, Girish Sankar, Sri\r\nHarsha Thota and Ram Balachandar\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tBridging Remote Sensing and Quantum Computing: Snow Depth\r\nEstimation with LSTM and QLSTM\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t150\t<\/td>\r\n<td>Dean Brand, Domenica Dibenedetto and Francesco Petruccione\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tCanonical Quantization of a Memristive Leaky\r\nIntegrate-and-Fire Neuron Circuit\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t86\t<\/td>\r\n<td>Ji Guan\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tCertifying Adversarial Robustness in Quantum Machine\r\nLearning: From Theory to Physical Validation\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t271\t<\/td>\r\n<td>Georgios Korpas, Wayne Lin, Iosif Sakos and Antonios\r\nVarvitsiotis\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tCertifying Optimality of VQA Solutions via Sparse SOS\r\nHierarchies\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t43\t<\/td>\r\n<td>Jan Schnabel, Roberto Fl\u00f3rez-Ablan and Marco Roth\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tChallenges and limitations of quantum kernel methods\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t200\t<\/td>\r\n<td>Paolo Braccia, Pablo Bermejo, Antonio Anna Mele, Nahuel\r\nDiaz, Andrew Deneris, Martin Larocca and Marco Cerezo\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tCharacterizing quantum resourcefulness via group-Fourier\r\ndecompositions\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t66\t<\/td>\r\n<td>Changjae Im, Hyeondo Oh and Daniel K. Park\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tClassical-quantum hybrid support vector data description\r\nfor one-class classification\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t125\t<\/td>\r\n<td>Giuseppe Sergioli, Roberto Giuntini, Andres Camillo Granda\r\nArango, Carlo Cuccu and Carla Sophie Rieger\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tClassification of Quantum Correlations via Quantum-inspired\r\nMachine Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t78\t<\/td>\r\n<td>Kristian Sotirov, Annie E. Paine, Savvas Varsamopoulos,\r\nAntonio A. Gentile and Osvaldo Simeone\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tConservative Quantum Offline Model-Based Optimization\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\tManual Submission\t<\/td>\r\n<td>Xiaoting Gao, Mingsheng Tian, Yu Xiang, Mattia Walschaers, and Qiongyi He\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tContinuous Variable Entanglement Detection and Classification through Neural Networks\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t37\t<\/td>\r\n\r\n<td>Prof. Dr. Gerhard Hellstern\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tData Clustering as a Quantum  Computing Use-Cas\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t220\t<\/td>\r\n<td>Arthur Strauss, Lukas Voss, Aniket Chatterjee and Hui Khoon\r\nNg\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDeep Reinforcement Learning for real-time context-aware\r\ngate calibration\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t77\t<\/td>\r\n<td>Hugo Thomas, Hela Mhiri, Leo Monbroussou, Zo\u00eb Holmes and\r\nElham Kashefi\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDequantization and expressivity in photonic quantum Fourier\r\nmodels\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t38\t<\/td>\r\n<td>Zhong-Xia Shang, Naixu Guo, Dong An and Qi Zhao\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDesign nearly optimal quantum algorithm for linear\r\ndifferential equations via Lindbladians\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t324\t<\/td>\r\n\r\n<td>Nouhaila Innan and Muhammad Shafique\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDesigning Privacy-Preserving Architectures in Quantum\r\nFederated Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t13\t<\/td>\r\n<td>Jonathan Lu, Lucy Jiao, Kristina Wolinski, Milan Kornja\u010da,\r\nHong-Ye Hu, Sergio Cantu, Fangli Liu, Susanne Yelin and\r\nSheng-Tao Wang\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDigital\u2013analog quantum learning on Rydberg atom arrays\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t94\t<\/td>\r\n<td>Yuxuan Yan, Sitian Qian, Qi Zhao and Xingjian Zhang\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDistilling the knowledge with quantum neural networks\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t104\t<\/td>\r\n<td>Marie Kempkes, Aroosa Ijaz, Elies Gil-Fuster, Carlos\r\nBravo-Prieto, Jakob Spiegelberg, Evert van Nieuwenburg and\r\nVedran Dunjko\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDouble Descent in Quantum Kernel Methods\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t187\t<\/td>\r\n<td>Yudai Suzuki, Bi Hong Tiang, Jeongrak Son, Ren\u00e9 Zander,\r\nRaphael Seidel, Nelly H. Y. Ng, Zo\u00eb Holmes and Marek Gluza\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDouble-bracket quantum algorithms for ground-state\r\npreparation via cooling\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t197\t<\/td>\r\n<td>Bharathi Kannan Jeevanandam, Nisarg Vyas, Sreeram Pg and\r\nSanthanam M.S\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDynamical Regimes and Memory Performance in Quantum\r\nReservoirs: Insights from Random Matrix Theory\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t82\t<\/td>\r\n<td>Jan Balewski, Chris Pestano, Mercy G. Amankwah, E. Wes\r\nBethel and Talita Perciano\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEHands: Quantum Protocol for Polynomial Computation on\r\nReal-Valued Encoded States\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t266\t<\/td>\r\n<td>Daniel Uzc\u00e1tegui, Katherine Mu\u00f1oz, Aldo Delgado and Dardo\r\nGoyeneche\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEntanglement detection via machine learning techniques\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t243\t<\/td>\r\n<td>Vladyslav Bohun, Illia Lukin, Mykola Lukhanko, Georgios\r\nKorpas, Philippe J.S. De Brouwer, Mykola Maksymenko and\r\nMaciej Koch-Janusz\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEntanglement scaling in matrix product state representation\r\nof smooth functions and their shallow quantum circuit\r\napproximations\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t15\t<\/td>\r\n<td>Haimeng Zhao and Dong-Ling Deng\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEntanglement-induced provable and robust quantum learning\r\nadvantages\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t71\t<\/td>\r\n<td>Iris Agresti, Mirela Selimovic, Michal Siemaszko, Joshua\r\nMorris, Borivoje Dakic, Riccardo Albiero, Andrea Crespi,\r\nFrancesco Ceccarelli, Roberto Osellame, Magdalena Stobinska\r\nand Philip Walther\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tExperimental quantum memristor-based reservoir computing\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t260\t<\/td>\r\n<td>Felix Paul, Bj\u00f6rn Minneker and Peter Jung\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tExploring Trainability of Quantum Fourier Models for\r\nDifferent Data Re-uploading Schemes\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t72\t<\/td>\r\n<td>Maria Demidik, Cenk T\u00fcys\u00fcz, Nico Piatkowski, Michele Grossi\r\nand Karl Jansen\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tExpressive equivalence of classical and quantum restricted\r\nBoltzmann machines\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t50\t<\/td>\r\n\r\n<td>Nils-Erik Sch\u00fctte, Niclas G\u00f6tting, Hauke M\u00fcntinga, Meike\r\nList, Daniel Brunner and Christopher Gies\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tExpressivity Limits of Quantum Reservoir Computing\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t335\t<\/td>\r\n<td>Mitali Nanda and Tirupati Bolisetti\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tFake News Detection using Hybrid Classical-Quantum Transfer\r\nLearning Approach\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t62\t<\/td>\r\n\r\n<td>Adam Wesolowski, Ronin Wu and Karim Essafi\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tFast, Accurate and Interpretable Graph Classification with\r\nTopological Kernels: An Even More Scalable Alternative to\r\nWeisfeiler-Lehman Kernels\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t209\t<\/td>\r\n<td>Javier Gonz\u00e1lez Otero, Adri\u00e1n P\u00e9rez Salinas and Miguel\r\n\u00c1ngel Gonz\u00e1lez Ballester\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tFlexible quantum Kolmogorov-Arnold networks via generalized\r\nfractional-order Chebyshev functions and trainable QSVT\r\nbasis\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t139\t<\/td>\r\n\r\n<td>Jiabin You, Jian Feng Kong and Jun Ye\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tForecasting the Lorenz System Using a Hierarchical Tensor\r\nNetwork Model\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t248\t<\/td>\r\n<td>Mansoor Ali Khan, Muhammad Naveed Aman and Biplab Sikdar\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tFrom Bits to Qubits: Comparative Insights into Embedding\r\nStrategies for Machine Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t154\t<\/td>\r\n<td>Naqueeb Ahmad Warsi, Ayanava Dasgupta and Masahito Hayashi\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tGeneralization Bounds for Quantum Learning via R\u00e9nyi\r\nDivergences\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t175\t<\/td>\r\n\r\n<td>Tongyan Wu, Amine Bentellis, Alona Sakhnenko and Jeanette\r\nLorenz\r\n\r\n<\/td>\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tGeneralization Bounds in Hybrid-Quantum Machine Learning\r\nModels\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t52\t<\/td>\r\n<td>Sabri Meyer, Francesco Scala, Franceso Tacchino and\r\nAurelien Lucchi\r\n<\/td>\r\n\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tGradient Scalability on Super-polynomially Complex Quantum\r\nLandscapes\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t229\t<\/td>\r\n<td>Eunok Bae, Nari Choi, Jeonghyun Shin and Minjin Choi\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tGrover's algorithm with W state-based initialization for\r\nsolving the exact-cover problem\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t196\t<\/td>\r\n<td>Ignacio Acedo\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHardware Adapted Quantum Machine Learning with Pulse-Level\r\noptimization\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t2\t<\/td>\r\n<td>Giacomo Franceschetto, Marcin P\u0142odzie\u0144, Maciej Lewenstein,\r\nAntonio Ac\u00edn and Pere Mujal\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHarnessing quantum back-action for time-series processing\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t41\t<\/td>\r\n<td>Daniil Rabinovich, Luis Ernesto Campos Espinoza, Georgii\r\nParadezhenko and Kirill Lakhmanskiy\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHeuristic ansatz design for trainable ion-native\r\ndigital-analog quantum circuits\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t142\t<\/td>\r\n\r\n<td>Chen-Yu Liu\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHybrid Parameterized Quantum States for Variational Quantum\r\nLearning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t314\t<\/td>\r\n\r\n<td>Siddhant Dutta and Sadok Ben Yahia\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHybrid Quantum Kolmogorov-Arnold Networks for High Energy\r\nPhysics Analysis at the LHC\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t303\t<\/td>\r\n<td>Parvathy Gopakumar, Rubell Marion Lincy G, Salvatore Sinno\r\nand Shruthi Thuravakkath\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHybrid Quantum Transfer Learning Models for Credit Risk\r\nAssessment\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t172\t<\/td>\r\n<td>Ankith Mohan, Tobias Haug, Kishor Bharti and Jamie Sikora\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHybrid quantum-classical heuristics for optimizing large\r\nseparable operators\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t16\t<\/td>\r\n<td>Hongsuk Yi\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHybrid Quantum-Classical Traffic Flow Classification with\r\nDeep Feature Extraction\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t293\t<\/td>\r\n<td>Zhan Yu, Naixu Guo, Gabriel Matos, Nikhil Khatri, Pranav\r\nKalidindi, Yizhan Han, Lirand\u00eb Pira, Soumik Adhikary, Steve\r\nClark and Patrick Rebentrost\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tImplementing Quantum Transformers on Trapped Ion Devices\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t262\t<\/td>\r\n<td>Nathan Haboury, Mo Kordzanganeh, Alexey Melnikov and Pavel\r\nSekatski\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tInformation plane and compression-gnostic feedback in\r\nquantum machine learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t274\t<\/td>\r\n<td>Yule Mayevsky, Akram Youssry, Ritik Sareen, Gerardo\r\nPaz-Silva and Alberto Peruzzo\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tInterpretable Machine Learning for Quantum Control\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t134\t<\/td>\r\n<td>Alona Sakhnenko, Christian Mendl and Jeanette Miriam Lorenz\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tIs data-efficient learning feasible with quantum models?\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t340\t<\/td>\r\n<td>Abdullah Kazi and Jayesh Hire\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLearning Boolean Functions with Non-Local Dependencies via\r\nHybrid Quantum-Classical Neural Networks\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t20\t<\/td>\r\n<td>Haimeng Zhao, Yuzhen Zhang and John Preskill\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLearning to erase quantum states: thermodynamic\r\nimplications of quantum learning theory\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t70\t<\/td>\r\n<td>Cenk T\u00fcys\u00fcz, Maria Demidik, Luuk Coopmans, Enrico Rinaldi,\r\nVincent Croft, Yacine Haddad, Matthias Rosenkranz and Karl\r\nJansen\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLearning to generate high-dimensional distributions with\r\nlow-dimensional quantum Boltzmann machines\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t270\t<\/td>\r\n<td>Armando Angrisani\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLearning Unitaries with Quantum Statistical Queries\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t273\t<\/td>\r\n<td>Alexandra Ram\u00f4a, Luis Santos and Akihito Soeda\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLow Cost Experimental Design for Frequency Estimation\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t152\t<\/td>\r\n<td>Vincent Han Leong Lau, Wenyu Guo, Ratnajit Sarkar, Aaron\r\nTranter, Qian Ling Kee, Rigui Zhou, Ping Koy Lam, Mile Gu\r\nand Tao Wang\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tMachine Learning-Assisted Parametric Modulation in Atomic\r\nMagnetometry\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t35\t<\/td>\r\n<td>Si Min Chan, Apimuk Sornsaeng and Dario Poletti\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tMANTIS: Multiple Anomaly-Detection Networks for Tensor\r\nInspired Solutions\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t59\t<\/td>\r\n<td>Letian Tang\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tMore-efficient Quantum Multivariate Mean Value Estimator\r\nfrom Generalized Grover Operator\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t49\t<\/td>\r\n<td>Yong Wang, Zhenghao Yin, Tobias Haug, Ciro Pentangelo,\r\nSimone Piacentini, Andrea Crespi, Francesco Ceccarelli,\r\nRoberto Osellame and Philip Walther\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tMultiple photons enhance data efficiency in quantum machine\r\nlearning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t18\t<\/td>\r\n<td>V Vijendran, Dax Enshan Koh, Eunok Bae, Hyukjoon Kwon, Ping\r\nKoy Lam and Syed M Assad\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tNear-Optimal Parameter Tuning of Level-1 QAOA for Ising\r\nModels\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t306\t<\/td>\r\n<td>Dohyoung Lee, Daniel K. Park and Taeyoung Park\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tNeural Quantum Embedded Self-supervised Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t198\t<\/td>\r\n\r\n<td>Junseo Lee and Nhat A. Nghiem\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tNew aspects of quantum topological data analysis: Betti\r\nnumber estimation, and testing and tracking of homology and\r\ncohomology classes\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t149\t<\/td>\r\n\r\n<td>Datong Chen and Huangjun Zhu\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tNonstabilizerness Enhances Thrifty Shadow Estimation\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t208\t<\/td>\r\n<td>Petros Georgiou, Aaron Mark Thomas, Sharu Theresa Jose and\r\nOsvaldo Simeone\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOn the Generalization of Adversarially Trained Quantum\r\nClassifiers\t<\/b><\/td> <\/tr>\r\n\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t80\t<\/td>\r\n<td>Maxime Meyer, Soumik Adhikary, Naixu Guo and Patrick\r\nRebentrost\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOnline Learning of Pure States is as Hard as Mixed States\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t242\t<\/td>\r\n<td>Jan Li, Tim Coopmans, Patrick Emonts, Kenneth Goodenough,\r\nJordi Tura and Evert van Nieuwenburg\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOptimising entanglement distribution policies under\r\nclassical communication constraints assisted by\r\nreinforcement learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t102\t<\/td>\r\n<td>Seokhoon Jeong and Daniel Kyungdeock Park\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOptimization Framework for Data-Adaptive and\r\nHardware-Efficient Quantum Data Embedding\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t130\t<\/td>\r\n<td>Marc Drudis, Alberto Baiardi, Mattia Chiurco, Francesco\r\nTacchino, Stefan Woerner and Christa Zoufal\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOptimizing Quantum Time Dynamics with Classical Support\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t48\t<\/td>\r\n<td>Daniel Pranjic and Semih Celiks\u00fcmer\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOptimizing Shadow Tomography for Many-Body Observables\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t302\t<\/td>\r\n<td>Andrii Kurkin, Kevin Shen, Susanne Pielawa, Hao Wang and\r\nVedran Dunjko\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tParameterized IQP-QCBM generative model: universality with\r\nhidden units and kernel-adaptive efficient training on\r\nclassical hardware\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t121\t<\/td>\r\n\r\n<td>Thais Lima Silva, Lucas Borges and Leandro Aolita\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tPartition function estimation with a quantum coin toss\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t251\t<\/td>\r\n<td>Shivani Pillay, Ilya Sinayskiy and Francesco Petruccione\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tPhysics-Informed Neural Networks for Simulating Open\r\nQuantum Systems\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t205\t<\/td>\r\n<td>Reyhaneh Aghaei Saem, Behrang Tafreshi, Zoe Holmes and\r\nSupanut Thanasilp\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tPitfalls in the hunt for scalable parameterized quantum\r\nmodels\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t263\t<\/td>\r\n\r\n<td>Nayoung Lee, Minsoo Shin, Asel Sagingalieva, Ayush Joshi\r\nTripathi, Karan Pinto and Alexey Melnikov\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tPredictive Control with Hybrid Depth-Infused Quantum Neural\r\nNetworks\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t211\t<\/td>\r\n\r\n<td>Jonathan Teo, Xin Wei Lee and Hoong Chuin Lau\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tProbabilistic Greedy Behaviour of the Equivariant Quantum\r\nCircuit\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t230\t<\/td>\r\n<td>Bence Bak\u00f3, D\u00e1niel Nagy, P\u00e9ter H\u00e1ga, Zs\u00f3fia Kallus and\r\nZolt\u00e1n Zimbor\u00e1s\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tProblem-informed Graphical Quantum Generative Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t165\t<\/td>\r\n<td>Carlos Bravo-Prieto, Elies Gil-Fuster, Sergi Masot-Llima\r\nand Tommaso Guaita\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tProspects for quantum advantage in ML from the\r\nrepresentability of quantum functions\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t328\t<\/td>\r\n\r\n<td>Lucas Tecot, Di Luo and Cho-Jui Hsieh\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tProvably Robust Training of Quantum Circuit Classifiers\r\nAgainst Parameter Noise\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t61\t<\/td>\r\n<td>Alvaro Romero Mato, Boyang Chen, Nathan Eskue and Vahid\r\nNasrabadi\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQAOA based Neural Architecture Search\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t167\t<\/td>\r\n<td>Daphne Wang, Anthony Walsh, Hugo Fruchet, Ariane Soret and\r\nPierre-Emmanuel Emeriau\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQCirCNN: a photonic-native quantum circular convolution\r\nnetwork based on circulant matrices\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t31\t<\/td>\r\n<td>Hsin-Yu Wu, Annie E. Paine, Evan Philip, Antonio A. Gentile\r\nand Oleksandr Kyriienko\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Algorithm for Solving Nonlinear Differential\r\nEquations Based on Physics-Informed Effective Hamiltonians\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t170\t<\/td>\r\n\r\n<td>Martin Larocca and Vojtech Havlicek\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum algorithms for representation-theoretic\r\nmultiplicities\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t9\t<\/td>\r\n<td>Jorge Mart\u00ednez de Lejarza, Hsin-Yu Wu, Oleksandr Kyriienko,\r\nGerman Rodrigo and Michele Grossi\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Chebyshev Probabilistic Models for Fragmentation\r\nFunctions\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t252\t<\/td>\r\n<td>Andrey Kardashin, Vladimir Palyulin and Konstantin Antipin\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum convolutional neural networks produce higher\r\nvariance in regression tasks\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t279\t<\/td>\r\n<td>Chaemoon Im and Joongheon Kim\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Differential Privacy in Quantum Federated Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t91\t<\/td>\r\n<td>Shaukat Ali\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Extreme Learning Machines: Insights from Industrial\r\nand Real-World Applications\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t185\t<\/td>\r\n<td>Francesco Aldo Venturelli, Marco Parigi, Stefano Martina,\r\nNatalia Mu\u00f1oz Moruno, Filippo Caruso, Alba Cervera Lierta\r\nand Miguel \u00c1ngel Gonz\u00e1lez Ballester\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum generative diffusion models for medical imaging\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t169\t<\/td>\r\n<td>Snehal Raj, Brian Coyle, L\u00e9o Monbroussou and Elham Kashefi\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Graph Neural Networks for the Travelling Salesman\r\nProblem\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t336\t<\/td>\r\n<td>Leonardo Lavagna, Francesca De Falco and Massimo Panella\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Hyperdimensional Computing for Pattern Completion\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t67\t<\/td>\r\n<td>Taehee Ko, Hyeong Won Yu, Inho Lee, Sangkook Choi and\r\nHyowon Park\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum medical image encoding and compression using\r\nFourier-based methods\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t288\t<\/td>\r\n<td>Minh Triet Chau, Hyeokjea Kwon, Sung Won Yun, Kevin\r\nFerreira, Thi Ha Kyaw and Jack Baker\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Neural Density Functionals in Density Functional\r\nTheory\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t155\t<\/td>\r\n<td>Diksha Sharma, Vivek Balasaheb Sabale, Atul Kumar and\r\nThirumalai M\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Neural Networks Facilitating Quantum State\r\nClassification\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t135\t<\/td>\r\n<td>Tianqi Chen and Jian Feng Kong\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Optimization Towards Large-Scale Molecular Docking\r\non a Quantum Computer\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t300\t<\/td>\r\n<td>Gabriel Mejia Ruiz, Eileen Kuhn and Achim Streit\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Principal Basis Learning (qPBL) for image\r\nclassification\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t227\t<\/td>\r\n<td>Santhanam Madabushi Srinivasan and Nisarg Vyas\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum reservoir computing with a single quantum chaotic\r\nnode\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t319\t<\/td>\r\n<td>Takahiro Kajisa\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Scalar Field Theoretic Extension of Boltzmann\r\nMachines to Solve a Class of Moment Matching Problems\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t301\t<\/td>\r\n<td>Shao Hen Chiew, Armando Angrisani, Zo\u00eb Holmes and Giuseppe\r\nCarleo\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum simulation in the Heisenberg picture via\r\nVectorization\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t151\t<\/td>\r\n<td>Donovan Slabbert, Dean Brand and Francesco Petruccione\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Spectral Clustering: Comparing Parameterized and\r\nNeuromorphic Quantum Kernels\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t189\t<\/td>\r\n<td>Myeonghwan Seong, Yujin Kim, Chanyoung Kim, Daniel K. Park\r\nand Youngjoon Hong\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum spectral operator learning for solving partial\r\ndifferential equations\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t131\t<\/td>\r\n<td>Tobias Fellner, David Kreplin, Samuel Tovey and Holm\r\nChristian\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum vs. classical: A comprehensive benchmark study for\r\npredicting time series with variational quantum machine\r\nlearning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t203\t<\/td>\r\n<td>Nikita Kuznetsov and Ernesto Campos\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum-Inspired Self-Attention in a Large Language Model\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t136\t<\/td>\r\n<td>Elizabeth Sarell, Ashwin Girish, Hector Spencer-Wood,\r\nMichael Puerrer, Christopher Messenger, Fiona Speirits and\r\nSarah Croke\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tReducing Circuit Depth of Amplitude Encoding for\r\nGravitational Waves\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t194\t<\/td>\r\n<td>Junghoon Justin Park, Jungwoo Seo, Sangyoon Bae, Samuel\r\nYen-Chi Chen, Huan-Hsin Tseng, Jiook Cha and Shinjae Yoo\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tResting-state fMRI Analysis using Quantum Time-series\r\nTransformer\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t318\t<\/td>\r\n<td>Mingxuan Liu, Valerio Scarani, Alexia Auffeves and Kiarn\r\nLaverick\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tRetrodictive Approach to Quantum State Smoothing\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t190\t<\/td>\r\n<td>Zihao Li, Huangjun Zhu and Masahito Hayashi\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tRobust and efficient verification of measurement-based\r\nquantum computation\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t277\t<\/td>\r\n<td>Sixuan Wu, Zanqiu Shen, Chenghong Zhu, Guangxi Li and Xin\r\nWang\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tScalable Non-Stabilizerness Recognition with Machine\r\nLearning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t228\t<\/td>\r\n<td>Xiyao Feng, Chenghong Zhu, Xian Wu, Jingbo Wang, Guangxi Li\r\nand Xin Wang\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tShuttleFormer: A Machine Learning Approach to Shuttle\r\nScheduling in Trapped-Ion\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t176\t<\/td>\r\n<td>Yi-Hsin Lin, Scott Smart and Prineha Narang\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tSigned Designs for Learning Quantum State Properties with\r\nApplications\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t249\t<\/td>\r\n<td>Anastasiia Nikolaeva, Evgeniy Kiktenko, Ilia Zalivako,\r\nAlexander Gircha, Alexander Borisenko, Ilya Semerikov,\r\nAleksey Fedorov and Nikolay Kolachevsky\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tSupervised binary classification of small-scale digit\r\nimages and weighted graphs with a trapped-ion quantum\r\nprocessor\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t308\t<\/td>\r\n<td>Aldo Lamarre and Dominik Safranek\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTailor Made Embeddings For Quantum Machine Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t290\t<\/td><td>Kaining Zhang, Junyu Liu, Liu Liu, Liang Jiang, Min-Hsiu\r\nHsieh and Dacheng Tao\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tThe curse of random quantum data and a cure from Pauli\r\ndistribution\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t337\t<\/td>\r\n<td>Leonardo Lavagna, Francesca De Falco and Massimo Panella\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tThe Effectiveness of Classical and Hybrid Models for MaxCut\r\nproblem\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t186\t<\/td>\r\n<td>Steven Kordonowy and Hannes Leipold\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tThe Lie Algebra of XY-mixer Topologies and Warm Starting\r\nQAOA for Constrained Optimization\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t171\t<\/td>\r\n<td>Mina Abbaszadeh, Mariam Zomorodi, Mehrnoosh Sadrzadeh,\r\nVahid Salari and Philip Kurian\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tToward Quantum Machine Translation via Quantum Natural\r\nLanguage Processing\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t46\t<\/td>\r\n<td>Mafalda Ram\u00f4a, Luis Santos, Nicholas Mayhall, Edwin Barnes\r\nand Sophia Economou\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTowards Optimization-Free Adaptive Ansatze\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t109\t<\/td>\r\n<td>Timothee Dao, Ege Yilmaz, Ibrahim Shehzad, Christophe Pere,\r\nKumar Ghosh, Corey O'Meara, Giorgio Cortiana, Stefan\r\nWoerner and Francesco Tacchino\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTowards quantum extreme learning and reservoir computing on\r\nutility-scale digital quantum processors\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t305\t<\/td>\r\n<td>Nikhil Khatri, Stefan Zohren and Gabriel Matos\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTrainability of Parameterised Linear Combinations of\r\nUnitaries\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t284\t<\/td>\r\n<td>Monit Sharma and Hoong Chuin Lau\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTransferable Equivariant Quantum Circuits for TSP:\r\nGeneralization Bounds and Empirical Validation\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t79\t<\/td>\r\n<td>Valentin Heyraud, H\u00e9loise Chomet and Jules Tilly\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tUnified Framework for Matchgate Classical Shadows\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t311\t<\/td>\r\n<td>\r\nGregory White, Petar Jurcevic, Charles Hill and Kavan Modi\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tUnifying non-Markovian characterisation with an efficient\r\nand self-consistent framework\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t122\t<\/td>\r\n<td>Aaron Thomas, Harry Youel and Sharu Jose\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tVAE-QWGAN: Addressing Mode Collapse in Quantum GANs via\r\nAutoencoding Priors\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t202\t<\/td>\r\n<td>Xavi Font Aragones and Miguel \u00c1ngel Gonz\u00e1lez Ballester\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tWavelet vision transformers and quantum pyramidal networks \r\nfor biomedical image analysis\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t299\t<\/td>\r\n<td>Slimane Thabet, L\u00e9o Monbroussou, Eliott Z. Mamon and Jonas\r\nLandman\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tWhen Quantum and Classical Models Disagree: Learning Beyond\r\nMinimum Norm Least Square\t<\/b><\/td> <\/tr>\r\n<\/table>\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-af59c62 e-flex e-con-boxed e-con e-parent\" data-id=\"af59c62\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-8eba6cd elementor-widget elementor-widget-menu-anchor\" data-id=\"8eba6cd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"PostersII\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bb64e27 elementor-widget elementor-widget-heading\" data-id=\"bb64e27\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Poster Session II: Tuesday<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-edd3a57 elementor-widget elementor-widget-wp-widget-custom_html\" data-id=\"edd3a57\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"wp-widget-custom_html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"textwidget custom-html-widget\"><table style=\"width:100%\" border=\"2\">\r\n  <tr>\r\n    <th style=\"background-color: #1F1B55;text-align: left;color:white\">EasyChairID<\/th>\r\n<th style=\"background-color: #1F1B55;text-align: left;color: white\">Authors<\/th> \r\n    <th style=\"background-color: #1F1B55;text-align: left;color: white\">Title<\/th> \r\n   \r\n  <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t259\t<\/td>\r\n<td>Morounfoluwa Obidare, Ernesto Campos and Daniil Rabinovich\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA distributed approach to quantum approximate optimization\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t182\t<\/td>\r\n<td>Jiasheng Isaac Cheong, Marcia Zhang, Wei Kit Tan,\r\nSolomonraj Wilson, Tianqi Chen and Mai Chan Lau\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA Hybrid Quantum-Classical AI Approach for Scalable and\r\nPrecise Prediction of Cell-Level Molecular Biomarkers from\r\nHistology\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t178\t<\/td>\r\n<td>Utkarsh Singh, Marco Armenta, Jean-Frederic Laprade, Aaron\r\nZ. Goldberg and Khabat Heshami\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tA Resource-Efficient Quantum Kernel for High-Dimensional\r\nLearning on NISQ Devices\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t201\t<\/td>\r\n<td>Krzysztof Bieniasz and Hans-Martin Rieser\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tActive learning with quantics tensor networks\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t195\t<\/td>\r\n<td>Junghoon Justin Park, Jiook Cha, Samuel Yen-Chi Chen,\r\nHuan-Hsin Tseng and Shinjae Yoo\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAddressing the Current Challenges of Quantum Machine\r\nLearning through Multi-Chip Ensembles\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t333\t<\/td>\r\n<td>Fute Wong\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAdvanced for-loop for QML algorithm search\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t327<\/td><td>Sebastian Nagies, Chiara Capecci, Kevin T. Geier, Marcel\r\nSeelbach Benkner, Javed Akram, Sebastian Rubbert, Dimitrios\r\nBantounas, Michael Moeller, Michael Johanning and Philipp\r\nHauke\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAdvances in Quantum Annealing: From PUBO Formulations to\r\nPractical Implementation\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t294\t<\/td>\r\n<td>Hayata Yamasaki, Natsuto Isogai and Mio Murao\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAdvantage of Quantum Machine Learning from General\r\nComputational Advantages\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t96\t<\/td>\r\n<td>Chirag Wadhwa, Laura Lewis, Elham Kashefi and Mina Doosti\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAgnostic Process Tomography\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t179\t<\/td>\r\n<td>Haiyue Kang, Younghun Kim, Eromanga Adermann, Martin Sevior\r\nand Muhammad Usman\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAlmost fault--tolerant quantum machine learning with\r\ndrastic overhead reduction\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t322\t<\/td>\r\n<td>Kensuke Kamisoyama, Lento Nagano and Koji Terashi\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAnalyzing Generalization Error in Quantum Kernel Methods\r\nusing Random Matrix Theory\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t173\t<\/td>\r\n<td>Dhiya Dharampal, Francesco Petruccione and Ilya Sinayskiy\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tApplications of Quantum Convolutional Neural Networks in\r\nMedical Image Processing\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t204\t<\/td>\r\n<td>James Sud, Kunal Marwaha and Adrian She\r\n    <td style=\"color: black;font-size: 14px\"><b>\tAverage-Case Algorithms for Local Hamiltonian Problems\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t25\t<\/td>\r\n<td>Fariha Azad, Matteo Inajetovic, Stefan K\u00fchn and Anna Pappa\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tBarren-plateau free variational quantum simulation of Z2\r\nlattice gauge theories\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t81\t<\/td>\r\n<td>Alexandra Ram\u00f4a and Luis Santos\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tBayesian Quantum Amplitude Estimation\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t258\t<\/td>\r\n<td>Antonio Mandarino, Christian Candeago, Paolo Da Rold,\r\nMichele Grossi and Pawel Horodecki\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tCharacterization of distillable bipartite system enhanced\r\nby collective measurement and machine learning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t101\t<\/td>\r\n<td>Matteo D'Anna, Yuxuan Zhang, Roeland Wiersema and Juan\r\nCarrasquilla Alvarez\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tCircuit compression for 2D quantum dynamics\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t329\t<\/td>\r\n<td>V Vijendran, Dax Enshan Koh, Ping Koy Lam and Syed M Assad\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tClassical and Quantum Heuristics for the Binary Paint Shop\r\nProblem\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t145\t<\/td>\r\n<td>Matteo Inajetovic, Johannes Jung, Matic Petri\u010d, Raphael\r\nSeidel and Ren\u00e9 Zander\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tCompilable QSVM with HHL in Qrisp\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t12\t<\/td>\r\n<td>Tuyen Nguyen and Maria Kieferova\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tConvergence and Generalization of Warm-Starting Variational\r\nQuantum Algorithm\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t92\t<\/td>\r\n<td>Aakash Ravindra Shinde, Arianne Meijer-van de Griend, Ilmo\r\nSalmenper\u00e4, Valter Uotila and Jukka K. Nurminen\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tData Embedding on Two-Qubit interaction using Ising XYZ\r\nHamiltonian model on Multiple Basis\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t312\t<\/td>\r\n<td>Anurag Saha Roy\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDifferentiable Digital Twins &amp; Machine Learning for Quantum\r\nComputing\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t313\t<\/td>\r\n<td>Kin Ian Lo, Hala Hawashin, Mina Abbazadeh, Tilen\r\nLimback-Stokin and Mehrnoosh Mehrnoosh Sadrzadeh\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDisCoCLIP: A Distributional Compositional Tensor Network\r\nEncoder for Vision-Language Understanding\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t58\t<\/td>\r\n<td>Amena Khatun and Muhammad Usman\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDistilling Quantum Adversarial Manipulations via Classical\r\nAutoencoders\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t56\t<\/td>\r\n<td>Ivana Nikoloska, Hamdi Joudeh, Ruud van Sloun and Osvaldo\r\nSimeone\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tDynamic Estimation Loss Control in Variational Quantum\r\nSensing via Online Conformal Inference\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t234\t<\/td>\r\n<td>Saad Amir, Anton Dekusar and Biswajit Basu\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEffect of Hybrid Model Structure on Reinforcement Learning\r\nPerformance\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t163\t<\/td>\r\n<td>Rafael Gomez Lurbe\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEfficient Estimation of the Quantum Fisher Information\r\nMatrix in Commuting-Block Variational Circuits\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t232\t<\/td>\r\n<td>Yewei Yuan, Outongyi Lv and Nana Liu\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEfficient Offline Reinforcement Learning via Quantum Reward\r\nEncoding\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t100\t<\/td>\r\n<td>Peter R\u00f6seler, Oliver Schaudt, Helmut Berg, Christian\r\nBauckhage and Matthias Koch\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEfficient Quantum Convolutional Neural Networks for Image\r\nClassification: Overcoming Hardware Constraints\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t119\t<\/td>\r\n<td>Francesco Ghisoni and Alessandro Berti\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEfficient State Preparation with Bucket Brigade QRAM and\r\nSegment Tree\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t320\t<\/td>\r\n<td>Emin Tarakci and Emine Can\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEmploying an Integrated MCDM with Quantum Fuzzy Logic in\r\nNext-Generation Communication\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t285\t<\/td>\r\n<td>Jayne Thompson, Paul Riechers, Andrew Garner, Thomas\r\nElliott and Mile Gu\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEnergetic advantages for quantum agents in online execution\r\nof complex strategies\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t326\t<\/td>\r\n<td>Sebastian Nagies, Emiliano Tolotti, Davide Pastorello and\r\nEnrico Blanzieri\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tEnhancing Expressivity of Quantum Neural Networks Based on\r\nthe SWAP test\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t236\t<\/td>\r\n<td>Yixuan Hu, Mengru Ma and Jiangwei Shang\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tError-mitigated quantum state tomography using neural\r\nnetworks\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t107\t<\/td>\r\n<td>Martin Mauser, Sol\u00e8ne Four, Lena Marie Predl, Riccardo\r\nAlbiero, Francesco Ceccarelli, Roberto Osellame, Philipp\r\nPetersen, Borivoje Dakic, Iris Agresti and Philip Walther\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tExperimental data re-uploading with provable enhanced\r\nlearning capabilities\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t332\t<\/td>\r\n<td>Ritu Thombre and Lirand\u00eb Pira\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tExplaining Quanvolutional Neural Networks: A Frobenius\r\nNorm-Based Approach\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t286\t<\/td>\r\n<td>Mariia Sobchuk, Arsalan Motamedi, Grecia Castelazo and\r\nPooya Ronagh\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tFast quantum algorithms for PDEs with pseudospectral\r\nFourier method via preconditioning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t98\t<\/td>\r\n<td>Hyeondo Oh and Daniel Kyungdeock Park\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tFinding Lottery Tickets in Quantum Machine Learning: Sparse\r\nTrainability in Variational Quantum Circuits\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t297\t<\/td>\r\n<td>Rupayan Bhattacharjee, Sergi Abadal, Carmen G. Almudever\r\nand Eduard Alarc\u00f3n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tFull-Stack Assessment Framework for Quantum Machine\r\nLearning Models\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t218\t<\/td>\r\n<td>Matteo Robbiati and Andrea Papaluca\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tFull-stack quantum machine learning on self-hosted quantum\r\ndevices with Qiboml\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t132\t<\/td>\r\n<td>Tobias Fellner, Samuel Tovey, Christian Holm and Michael\r\nSpannowsky\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tGenerating Quantum Reservoir State Representations with\r\nRandom Matrices\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t214\t<\/td>\r\n<td>Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi,\r\nJiayang Niu and Yongli Ren\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tGeometry-Aware Dictionary Learning and Quantum-Guided\r\nBagging for Qubit-Efficient Recommender Systems\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t272\t<\/td>\r\n<td>Yule Mayevsky, Akram Youssry, Ritik Sareen, Gerardo\r\nPaz-Silva and Alberto Peruzzo\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tGraybox Approach for Qudit System Identification and Control\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t341\t<\/td>\r\n<td>Payal D. Solanki and Anh Pham\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHarnessing Quantum Dynamics for Robust and Scalable Quantum Extreme Learning Machines\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t283\t<\/td>\r\n<td>Monit Sharma and Hoong Chuin Lau\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHybrid Learning and Optimization Methods for Solving\r\nCapacitated Vehicle Routing Problem\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t307\t<\/td>\r\n<td>Jian Feng Kong, Chee Kwan Gan, Stefano Carrazza and Jun\r\nYong Khoo\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tHybrid Quantum-Classical Neural Networks with Data\r\nReuploading for Binary Medical Image Classification\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t164\t<\/td>\r\n<td>Florian Heininger, Niels Halama, Sakshi Singh, Jeanette\r\nMiriam Lorenz and Matthias Weidem\u00fcller\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tImbalanced classification with quantum kernel methods\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t27\t<\/td>\r\n<td>Mafalda Ram\u00f4a, Panagiotis Anastasiou, Luis Santos, Edwin\r\nBarnes, Nicholas Mayhall and Sophia Economou\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tImproving Adaptive Variational Quantum Algorithms\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t160\t<\/td>\r\n<td>Francesco Scala, Giacomo Guarnieri, Dario Gerace and\r\nAurelien Lucchi\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tImproving Quantum Neural Networks performances by\r\nNoise-Induced Equalization\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t17\t<\/td>\r\n<td>Arthur Mendon\u00e7a Faria, Ignacio Fern\u00e1ndez Gra\u00f1a and Savvas\r\nVarsamopoulos\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tInductive Graph Representation Learning with Quantum Graph\r\nNeural Networks\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t235\t<\/td>\r\n<td>Gordon Yuan Ning Ma, Ioannis Leonidas and Dimitris G.\r\nAngelakis\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tInformation-Minimal Two-Body Moment Learning for Scalable\r\nQUBO Optimisation\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t117\t<\/td>\r\n<td>Aoi Hayashi, Akitada Sakurai and Kae Nemoto\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tInformation-theoretic evaluation of quantum machine\r\nlearning model complexity\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t22\t<\/td>\r\n<td>Doron Podoleanu\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tInterference Beats Hallucination? A Controlled Study of\r\nHybrid Quantum\u2013Classical Language Models for Code Generation\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t239\t<\/td>\r\n<td>Nicola Assolini, Luca Marzari, Isabella Mastroeni and\r\nAlessandra Di Pierro\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tInterval-based Analysis of Variational Quantum Algorithms\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t338\t<\/td>\r\n<td>Leonardo Lavagna, Francesca De Falco and Massimo Panella\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tIs the QAOA the Ultimate Solution for the MaxCut problem?\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t99\t<\/td>\r\n<td>Yuqi Li, Zhouhang Shi, Li Shen, Haitao Ma, Jinge Bao and\r\nYunlong Xiao\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLanguage Model for Large-Text Transmission in Noisy Quantum\r\nCommunications\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t157\t<\/td>\r\n<td>Jinge Bao and Francisco Escudero Guti\u00e9rrez\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLearning junta distributions, quantum junta states, and\r\nQAC0 circuits\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t106\t<\/td>\r\n<td>Eric Brunner, Luuk Coopmans, Gabriel Matos, Matthias\r\nRosenkranz, Frederic Sauvage and Yuta Kikuchi\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLindblad engineering for quantum Gibbs state preparation\r\nunder the eigenstate thermalization hypothesis\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t180\t<\/td>\r\n<td>Siddhartha Emmanuel Morales Guzman\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLow Rank Piecewise Polynomial Data Encoding\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t138\t<\/td>\r\n<td>Roselyn Nmaju, Sarah Croke and Fiona Speirits\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLow-depth measurement-based deterministic quantum state\r\npreparation\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t44\t<\/td>\r\n<td>Alice Barthe, Casper Gyurik, Jordi Tura, Vedran Dunjko and\r\nPatrick Emonts\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tLower Bounding Betti Numbers using Tensor Networks\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t199\t<\/td>\r\n<td>Prashasti Tiwari\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tMany Body Eigenvalue Problems with a Trapped Ion System\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t112\t<\/td>\r\n<td>Hector Spencer-Wood, John Jeffers and Sarah Croke\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tMeasurement disturbance tradeoffs in unsupervised quantum\r\nclassification\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t159\t<\/td>\r\n<td>Yang Qian, Xinbiao Wang, Yuxuan Du, Yong Luo and Dacheng Tao\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tMG-Net: Learn to Customize QAOA with Circuit Depth Awareness\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t222\t<\/td>\r\n<td>Korbinian Stein, Davide Bincoletto and Jakob Kottmann\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tModeling Quantum Circuit Parameterswith Size-Independent\r\nMachine Learning Models\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t245\t<\/td>\r\n<td>Illia Lukin, Vladyslav Bohun, Mykola Lukhanko and Maciej\r\nKoch-Janusz\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tMPS-based Fourier series loading\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t137\t<\/td>\r\n<td>Wenyu Guo, Qing Liu, Ximing Wang, Chufan Lyu, Jayne\r\nThompson, Andrew J.P. Garner, Aaron Tranter, Rigui Zhou,\r\nChengran Yang and Mile Gu\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tNeural network-assisted quantum compilation\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t141\t<\/td>\r\n<td>Seongwook Shin, Ryan Sweke and Hyunseok Jeong\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tNew perspectives on quantum kernels through the lens of\r\nentangled tensor kernels\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t7\t<\/td>\r\n<td>Natchapol Patamawisut and Yen-Jui Chang\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tNonlinear Quantum Image Encoding via Information Mixing\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t105\t<\/td>\r\n<td>Nicolo Colombo and Thomas Gargan\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOn Bounding Quantum Fidelity with Conformal Prediction\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t275\t<\/td>\r\n<td>Guilherme Adamatti Bridi, Debbie Lim, Lirand\u00eb Pira,\r\nRaqueline Azevedo Medeiros Santos, Franklin de Lima\r\nMarquezino and Soumik Adhikary\r\n\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOn the Necessity of Overparameterization in the Quantum\r\nWalk Optimization Algorithm\r\n\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t315\t<\/td>\r\n<td>Rebecca Erbanni, Gregory A. L. White, Jens Eisert and\r\nMatthias C. Caro\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOn the structure of easy and hard-to-learn positive MPOs\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t74\t<\/td>\r\n<td>Niclas G\u00f6tting, Steffen Wilksen, Alexander Steinhoff,\r\nFrederik Lohof and Christopher Gies\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOptically Probing Quantum Reservoir Memory\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t5\t<\/td>\r\n<td>Bodo Rosenhahn, Tobias J. Osborne and Christoph Hirche\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOptimization Driven Quantum Circuit Reduction\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t223\t<\/td>\r\n<td>Chenghong Zhu, Hongshun Yao, Yingjian Liu and Xin Wang\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tOptimizer-Dependent Generalization Bound for Quantum Neural\r\nNetworks\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t30\t<\/td>\r\n<td>Benjamin Stott, Gr\u00e9goire Barru\u00e9 and Tony Quertier\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tPhotonic Quantum Kernel methods for Malware Classification\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t241\t<\/td>\r\n<td>Marco Parigi, Stefano Martina, Francesco Aldo Venturelli\r\nand Filippo Caruso\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tPhysics-inspired Generative AI models via real\r\nhardware-based noisy quantum diffusion\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t87\t<\/td>\r\n<td>Taisei Nohara, Itsuki Noda and Satoshi Oyama\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tPositive-Unlabeled Learning for Training an Entanglement\r\nDetector\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t63\t<\/td>\r\n<td>Takao Tomono and Kazuya Tsujimura\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tPotential of multi-anomalies detection using quantum\r\nmachine learning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t146\t<\/td>\r\n<td>Aaron Thomas, Yu-Cheng Chen, Hubert Valencia, Sharu Jose\r\nand Ronin Wu\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQCA-MolGAN: Quantum Circuit Associative Molecular GAN with\r\nMulti-Agent Reinforcement Learning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t325\t<\/td>\r\n<td>Nouhaila Innan and Muhammad Shafique\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQ-Compression: Quantum-Aware Model Compression Techniques\r\nfor Scalable Quantum Machine Learning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t23\t<\/td>\r\n<td>Petr Ivashkov, Po-Wei Huang, Kelvin Koor, Lirand\u00eb Pira and\r\nPatrick Rebentrost\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQKAN: Quantum Kolmogorov-Arnold Networks\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t68\t<\/td>\r\n<td>Anderson Melchor Hernandez, Filippo Girardi, Davide\r\nPastorello and Giacomo De Palma\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantitative convergence of trained quantum neural networks\r\nto a Gaussian process\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t128\t<\/td>\r\n<td>Ge Bai, Francesco Buscemi and Valerio Scarani\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Bayes\u2019 rule from a minimum change principle:\r\ngradient-free belief updates for quantum learning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t85\t<\/td>\r\n<td>Natchapol Patamawisut and Ruchipas Bavontaweepanya\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Circuit Optimization for Variational Grover's\r\nSearch via ZX Calculus\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t280\t<\/td>\r\n<td>Kouhei Nakaji, Jonathan Wurtz, Haozhe Huang, Luis Mantilla\r\nCalderon, Karthik Panicker, Elica Kyoseva and Al\u00e1n\r\nAspuru-Guzik\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum circuits as a game: A reinforcement learning agent\r\nfor quantum compilation and its application to\r\nreconfigurable neutral atom arrays\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t238\t<\/td>\r\n<td>Hoang Anh Nguyen, Nhu Duc Dinh, Le Tu Uyen Tu and Van Duy\r\nNguyen\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Deep Learning Force Field\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t14\t<\/td>\r\n<td>Neeshu Rathi and Sanjeev Kumar\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Ensemble Learning with QRAM-Based Subsampling and\r\nShallow Clustering Weak Learners\t<\/b><\/td> <\/tr>\r\n\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t158\t<\/td>\r\n<td>Borja Aizpurua, Saeed Jahromi, Sukhbinder Singh and Rom\u00e1n\r\nOr\u00fas\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Large Language Models via Tensor Network\r\nDisentanglers\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t246\t<\/td>\r\n<td>Riccardo Molteni, Simon C. Marshall and Vedran Dunjko\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum machine learning advantages beyond hardness of\r\nevaluation\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t267\t<\/td>\r\n<td>Hon Wai Lau, Aoi Hayashi, William John Munro, Jayne\r\nThompson and Mile Gu\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Memory Resource Advantage in Reinforcement Learning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t75\t<\/td>\r\n<td>Jo\u00e3o F. Bravo, Daniel Basilewitsch, Christian Tutschku and\r\nFrederick Struckmeier\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Neural Networks in Practice: A Comparative Study\r\nwith Classical Models from Standard Data Sets to Industrial\r\nImages\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t254\t<\/td>\r\n<td>Danijela Markovic\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum neuromorphic computing with parametrically coupled\r\nbosonic modes in superconducting resonators\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t224\t<\/td>\r\n<td>Sreetama Das, Gian Luca Giorgi and Roberta Zambrini\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum reservoir computing for temporal series processing\r\nusing spin-boson systems\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t255\t<\/td>\r\n<td>Micha\u0142 Siemaszko, Martin Mauser, Iris Agresti, Philip\r\nWalther and Magdalena Stobi\u0144ska\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum reservoir computing with multiple photonic\r\nmemristors and skip connections\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t330\t<\/td>\r\n<td>Luke Antoncich, Milan Kornjaca, Jonathan Wurtz, Jing Chen,\r\nPascal Elahi and Casey Myers\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Reservoir Computing with Small Datasets\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t156\t<\/td>\r\n<td>Maitreyee Sarkar, Lisa Roy, Aksah Gutal, Atul Kumar and\r\nManikandan Paranjothy\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum Simulations of Chemical Reactions: Achieving\r\nAccuracy with NISQ Devices\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t268\t<\/td>\r\n<td>Ritik Sareen, Akram Youssry, Yule Mayevsky and Alberto\r\nPeruzzo\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum State Preparation using Dynamical Invariants and\r\nMachine Learning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t265\t<\/td>\r\n<td>Luis Ernesto Campos Espinoza and Dmitry Guskov\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum variational parameters as classical data outputs\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t339\t<\/td>\r\n<td>Soham Pawar and Dibakar Das\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum-Hybrid Siamese Networks with Inter-Channel Weight\r\nInteraction\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t34\t<\/td>\r\n<td>Hideki Okawa, Qing-Guo Zeng, Xian-Zhe Tao and Man-Hong Yung\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuantum-Inspired Optimization for High Energy Physics\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t278\t<\/td>\r\n<td>Seungcheol Oh, Chaemoon Im and Joongheon Kim\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQubit Trajectory Analysis in Quantum Neural Networks\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t90\t<\/td>\r\n<td>Chengsi Mao, Changhao Yi and Huangjun Zhu\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQudit shadow estimation based on the Clifford group and the\r\npower of a single magic gate\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t309\t<\/td>\r\n<td>Nikhil Khatri, Gabriel Matos, Luuk Coopmans and Stephen\r\nClark\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQuixer: A Quantum Transformer Model\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t233\t<\/td>\r\n<td>Hoang-Anh Nguyen, Duy-Tung Nguyen, Tran-Hien Vo, Dang-Khanh\r\nNguyen, Nhu-Duc Dinh and Van-Duy Nguyen\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tQutrit-Based Quantum Circuit Design via Reinforcement\r\nLearning for Simulating Three-Flavor Collective Neutrino\r\nOscillations\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t36\t<\/td>\r\n<td>Felix J. Beckmann and Jo\u00e3o F. Bravo\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tRavines in quantum cost landscapes: Opportunities for\r\nenhanced VQA predictions on quantum data\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t64\t<\/td>\r\n<td>Maxwell West, Antonio Anna Mele, Mart\u00edn Larocca and Marco\r\nCerezo\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tReal classical shadows\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t316\t<\/td>\r\n<td>Abdullah Kazi and Jayesh Hire\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tRecurrent Measurement-Based Quantum Machine Learning\r\n(MBQML) with Feedback\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t124\t<\/td>\r\n<td>Jan Nogu\u00e9 G\u00f3mez\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tReinforcement Learning Based Quantum Circuit Optimization\r\nvia ZX-Calculus\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t140\t<\/td>\r\n<td>Weijie Xiong, Zoe Holmes, Armando Angrisani, Yudai Suzuki,\r\nThiparat Chotibut and Supanut Thanasilp\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tRole of scrambling, noise, and symmetry in temporal\r\nlearning with quantum systems\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t177\t<\/td>\r\n<td>Hongshun Yao, Yingjian Liu, Tengxiang Lin and Xin Wang\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tSample-Efficient Estimation of Nonlinear Quantum State\r\nFunctions\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t225\t<\/td>\r\n<td>Chenghong Zhu, Xian Wu, Hao-Kai Zhang, Sixuan Wu, Guangxi\r\nLi and Xin Wang\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tScalable Quantum Architecture Search based on Relative\r\nFluctuation of Landscapes\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t216\t<\/td>\r\n<td>Antonin Sulc\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tSelf-Optimizing Quantum Circuits via Reinforcement Learning\r\nand Language Models\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t289\t<\/td>\r\n<td>Su Yeon Chang, Supanut Thanasilp, Zo\u00eb Holmes and Marco\r\nCerezo\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tSimulation cost of classically simulable quantum machine\r\nlearning models\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t206\t<\/td>\r\n<td>Jonathan Teo, Xin Wei Lee and Hoong Chuin Lau\r\n\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tSize-Invariant Properties at Depth 1 of the Equivariant\r\nQuantum Circuit\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t264\t<\/td>\r\n<td>Callum Duffy, Marcin Jastrzebski and Sarah Malik\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tSpectral Bias in Parameterised Quantum Circuits\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t89\t<\/td>\r\n<td>Vardaan Mongia, Abhishek Kumar, Shashi Prabhakar and R.P.\r\nSingh\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tStrengthening the no-go theorem for QRNGs\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t191\t<\/td>\r\n<td>L\u00e9o Monbroussou, Jonas Landman, Letao Wang, Alex Bredariol\r\nGrilo and Elham Kashefi\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tSubspace Preserving Quantum Convolutional Neural Network\r\nArchitectures\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t153\t<\/td>\r\n<td>Jun Qi, Chao-Han Huck Yang and Pin-Yu Chen\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTensor Network-Enhanced Variational Quantum Circuits:\r\nTheory, Hybrid Architectures, and Scalable Optimization for\r\nQuantum Machine Learning\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t310\t<\/td>\r\n<td>Mario Herrero-Gonz\u00e1lez, Ross Grassie, Kieran McDowall,\r\nSjoerd Beentjes, Ava Khamseh and Elham Kashefi\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tThe Born Ultimatum: Simulability in Quantum Generative\r\nModels. Capturing Higher-Order Moments from Data.\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t250\t<\/td>\r\n<td>Ilya Sinayskiy\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tThe effect of classical optimizers and Ansatz depth on QAOA\r\nperformance in noisy devices\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t269\t<\/td>\r\n<td>Muhammad Al-Zafar Khan, Jamal Al-Karaki, Assala Benmalek,\r\nAbdullah Al Omar Ghalib and Marwan Omar\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tThe Ubiquity of QPINNs: A Multi-Domain Study\t<\/b><\/td> <\/tr>\r\n<tr>\r\n    <td style=\"color: black;font-size: 14px\">\t127\t<\/td>\r\n<td>Zherui Wang, Jordi Tura and Patrick Emonts\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTopological data analysis with variational quantum circuits\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t123\t<\/td>\r\n<td>Caesnan Leditto, Angus Southwell, Behnam Tonekaboni,\r\nMuhammad Usman, Kavan Modi and Gregory White\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTopological Signal Processing on Quantum Computers for Higher-Order Network Analysis\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t231\t<\/td>\r\n<td>Eleanor Kedem, Ryan Sweke and Francesco Petruccione\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tToward Undetectable Backdoors in Variational Quantum Models\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t53\t<\/td>\r\n<td>Adri\u00e1n P\u00e9rez-Salinas, Berta Casas, Xavier Bonet-Monroig and\r\nHao Wang\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTowards a Framework for Analyzing Quantum Machine Learning Algorithms\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t162\t<\/td>\r\n<td>Brian Coyle, Snehal Raj and El Amine Cherrat\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tTraining parameterized quantum circuits with forward\r\ngradients\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t237\t<\/td>\r\n<td>Yunting Li and Huangjun Zhu\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tUniversal and Efficient Quantum State Verification via\r\nSchmidt Decomposition and Mutually Unbiased Bases\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t54\t<\/td>\r\n<td>Adri\u00e1n P\u00e9rez-Salinas, Mahtab Yaghubi Rad, Alice Barthe and\r\nVedran Dunjko\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tUniversal approximation of continuous functions with\r\nminimal quantum circuits\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t282\t<\/td>\r\n<td>Kosuke Ito, Hiroshi Yano, Yudai Suzuki, Akira Tanji and\r\nNaoki Yamamoto\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tUnsupervised domain adaptation for quantum data under state\r\nand distribution shifts\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t69\t<\/td>\r\n<td>M. Emre Sahin, Cenk T\u00fcys\u00fcz, Edoardo Altamura, David Galvin,\r\nOscar Wallis, Alex Gregory, Paul Edwards, Stefano Mensa and\r\nChrista Zoufal\r\n<\/td>\r\n\r\n    <td style=\"color: black;font-size: 14px\"><b>\tUsable Information in Quantum Machine Learning\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t247\t<\/td>\r\n<td>Vladyslav Los and Maciej Koch-Janusz\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tVariational bounds of quantum information-theoretic\r\nquantities for quantum error correcting code analytics\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t118\t<\/td>\r\n<td>Benchi Zhao and Keisuke Fujii\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tVariational quantum Hamiltonian engineering\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t57\t<\/td>\r\n<td>Alessio Pecilli and Matteo Rosati\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tVariational quantum self-attention for the prediction of\r\nclassical and quantum data sequences\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t84\t<\/td>\r\n<td>Fong Yew Leong, Dax Enshan Koh, Jian Feng Kong, Siong Thye\r\nGoh, Jun Yong Khoo, Wei-Bin Ewe, Hongying Li, Jayne\r\nThompson and Dario Poletti\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tVariational Quantum Solver for Time-Fractional Differential\r\nEquations with Efficient Memory Scaling\t<\/b><\/td> <\/tr>\r\n<tr>  <td style=\"color: black;font-size: 14px\">\t73\t<\/td>\r\n<td>Annie Paine, Smit Chaudhary and Antonio Gentile\r\n\r\n<\/td>\r\n    <td style=\"color: black;font-size: 14px\"><b>\tWeak Form Regularisation for Solving Differential Equations\r\nwith Quantum Neural Networks\t<\/b><\/td> <\/tr>\r\n\r\n\r\n\r\n  \r\n  <\/table>\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-dba4701 e-flex e-con-boxed e-con e-parent\" data-id=\"dba4701\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-56ff252 elementor-widget elementor-widget-spacer\" data-id=\"56ff252\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ead6251 elementor-widget elementor-widget-image\" data-id=\"ead6251\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/quantum2025.org\/\">\n\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"116\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/IYQST-horiz-rgb-300x116.png\" class=\"attachment-medium size-medium wp-image-1167\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/IYQST-horiz-rgb-300x116.png 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/IYQST-horiz-rgb-1024x396.png 1024w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/IYQST-horiz-rgb-768x297.png 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/IYQST-horiz-rgb-1536x594.png 1536w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/IYQST-horiz-rgb-2048x792.png 2048w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-a21e7f0 e-flex e-con-boxed e-con e-parent\" data-id=\"a21e7f0\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f487545 elementor-widget elementor-widget-spacer\" data-id=\"f487545\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9c933a8 e-con-full e-flex e-con e-parent\" data-id=\"9c933a8\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-939e17b elementor-widget elementor-widget-heading\" data-id=\"939e17b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Sponsors<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b27660c elementor-widget elementor-widget-spacer\" data-id=\"b27660c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-988d9f7 e-grid e-con-full e-con e-child\" data-id=\"988d9f7\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7d6dc6a elementor-widget elementor-widget-image\" data-id=\"7d6dc6a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/cqt.sg\">\n\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"129\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/01_CQT_SG_Logo_FullColor_BlackText-300x129.png\" class=\"attachment-medium size-medium wp-image-1166\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/01_CQT_SG_Logo_FullColor_BlackText-300x129.png 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/01_CQT_SG_Logo_FullColor_BlackText-1024x439.png 1024w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/01_CQT_SG_Logo_FullColor_BlackText-768x329.png 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/01_CQT_SG_Logo_FullColor_BlackText-1536x659.png 1536w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/01_CQT_SG_Logo_FullColor_BlackText-2048x878.png 2048w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bcecfcb elementor-widget elementor-widget-image\" data-id=\"bcecfcb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/quantumai.google\/\">\n\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"124\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Google-Quantam-AI-Logo@2x-300x124.png\" class=\"attachment-medium size-medium wp-image-1342\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Google-Quantam-AI-Logo@2x-300x124.png 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Google-Quantam-AI-Logo@2x-1024x424.png 1024w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Google-Quantam-AI-Logo@2x-768x318.png 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Google-Quantam-AI-Logo@2x-1536x635.png 1536w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Google-Quantam-AI-Logo@2x-2048x847.png 2048w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eb1264d elementor-widget elementor-widget-image\" data-id=\"eb1264d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.horizonquantum.com\/\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"111\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/10\/Horizon-Quantum-Primary-Full-color-300x111.png\" class=\"attachment-medium size-medium wp-image-1448\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/10\/Horizon-Quantum-Primary-Full-color-300x111.png 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/10\/Horizon-Quantum-Primary-Full-color-1024x378.png 1024w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/10\/Horizon-Quantum-Primary-Full-color-768x284.png 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/10\/Horizon-Quantum-Primary-Full-color-1536x567.png 1536w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/10\/Horizon-Quantum-Primary-Full-color-2048x756.png 2048w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-32b7b53 e-grid e-con-full e-con e-child\" data-id=\"32b7b53\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2747564 elementor-widget elementor-widget-image\" data-id=\"2747564\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.jpmorganchase.com\/\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"43\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/JPMC_Logo_Standard_Black_RGB-300x43.png\" class=\"attachment-medium size-medium wp-image-986\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/JPMC_Logo_Standard_Black_RGB-300x43.png 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/JPMC_Logo_Standard_Black_RGB-768x109.png 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/JPMC_Logo_Standard_Black_RGB.png 1000w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ae676e9 elementor-widget elementor-widget-image\" data-id=\"ae676e9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/majulab.cnrs.fr\/\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"81\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Majulab-Final-300x81.png\" class=\"attachment-medium size-medium wp-image-1185\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Majulab-Final-300x81.png 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Majulab-Final-1024x276.png 1024w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Majulab-Final-768x207.png 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Majulab-Final-1536x415.png 1536w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Majulab-Final-2048x553.png 2048w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-06c4ff2 elementor-widget elementor-widget-image\" data-id=\"06c4ff2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/multiversecomputing.com\/\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"40\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Horizontal-full-Light-Mode-22-300x40.png\" class=\"attachment-medium size-medium wp-image-987\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Horizontal-full-Light-Mode-22-300x40.png 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Horizontal-full-Light-Mode-22-1024x137.png 1024w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Horizontal-full-Light-Mode-22-768x102.png 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Horizontal-full-Light-Mode-22-1536x205.png 1536w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/Logo-Horizontal-full-Light-Mode-22.png 1800w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ca4caa0 e-grid e-con-full e-con e-child\" data-id=\"ca4caa0\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2ba5c8c elementor-widget elementor-widget-image\" data-id=\"2ba5c8c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/nqo.sg\/\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"116\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NQO-logo_RGB-300x116.png\" class=\"attachment-medium size-medium wp-image-2483\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NQO-logo_RGB-300x116.png 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NQO-logo_RGB-1024x396.png 1024w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NQO-logo_RGB-768x297.png 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NQO-logo_RGB-1536x594.png 1536w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NQO-logo_RGB.png 1772w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-285cc7d elementor-widget elementor-widget-image\" data-id=\"285cc7d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.nus.edu.sg\/\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"186\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NUS_logo_full-horizontal-300x186.jpg\" class=\"attachment-medium size-medium wp-image-2484\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NUS_logo_full-horizontal-300x186.jpg 300w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NUS_logo_full-horizontal-1024x635.jpg 1024w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NUS_logo_full-horizontal-768x476.jpg 768w, https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/11\/NUS_logo_full-horizontal.jpg 1390w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-85fe7c7 elementor-widget elementor-widget-image\" data-id=\"85fe7c7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/qai-ventures.com\/\">\n\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"74\" src=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/QAI_Logo_with_Symbol_Black_Horizontal-300x74.jpg\" class=\"attachment-medium size-medium wp-image-1168\" alt=\"\" srcset=\"https:\/\/qtml2025.cqt.sg\/wp-content\/uploads\/2025\/09\/QAI_Logo_with_Symbol_Black_Horizontal-300x74.jpg 300w, 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