https://m2.mtmt.hu/ hun 2026-10-23 03:50 BookChapter 35778536 APPROVED true The Hong Kong University of Science and Technology, Hong Kong Beihang University, China Conference code: 200372 Cited By :6 Export Date: 21 February 2025 Correspondence Address: Xie, F.; Beihang UniversityChina; email: xfy_73@buaa.edu.cn Correspondence Address: Chen, H.; The Hong Kong University of Science and TechnologyHong Kong; email: jhc@cse.ust.hk Funding details: National Natural Science Foundation of China, NSFC, 62202403 Funding details: National Natural Science Foundation of China, NSFC Funding details: Science, Technology and Innovation Commission of Shenzhen Municipality, SGDX20210823103201011 Funding details: Science, Technology and Innovation Commission of Shenzhen Municipality Funding details: Research Grants Council, University Grants Committee, 研究資助局, R6003-22 Funding details: Research Grants Council, University Grants Committee, 研究資助局 Funding text 1: This work was supported by National Natural Science Foundation of China (No. 62202403), Shenzhen Science and Technology Innovation Committee Funding (Project No. SGDX20210823103201011), the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. R6003-22 and C4024-22GF). 0 false 2025-02-21T13:50:32.272+0000 2025-02-21T13:49:06.939+0000 2025-02-21T13:24:29.613+0000 true 10000109 Győrffy Balázs /api/author/10000109 Author Győrffy Balázs (Onkológia) true 10000109 5111370 2025-02-21T13:49:07.073+0000 2025-02-21T13:49:07.032+0000 Author 10000109 /api/author/10000109 Győrffy Balázs (Onkológia) Győrffy Balázs true 10000109 true SUSPECT 2025-02-21T13:49:07.032+0000 false false true 31 31 /api/publicationtype/31 PublicationType Egyéb konferenciaközlemény 4 true 31 BookChapter true 10000197 Conference paper true 31 31 /api/publicationtype/31 PublicationType Egyéb konferenciaközlemény 4 true 31 BookChapter /api/subtype/10000197 Konferenciaközlemény SubType Konferenciaközlemény (Egyéb konferenciaközlemény) 452 true 10000197 true 1 /api/category/1 Category Tudományos true 1 Zhang, Y. Code 200372 Code 200372 2024 Multimodal learning significantly benefits cancer survival prediction, especially the integration of pathological images and genomic data. Despite advantages of multimodal learning for cancer survival prediction, massive redundancy in multimodal data prevents it from extracting discriminative and compact information: (1) An extensive amount of intra-modal task-unrelated information blurs discriminability, especially for gigapixel whole slide images (WSIs) with many patches in pathology and thousands of pathways in genomic data, leading to an “intra-modal redundancy” issue. (2) Duplicated information among modalities dominates the representation of multimodal data, which makes modality-specific information prone to being ignored, resulting in an “inter-modal redundancy” issue. To address these, we propose a new framework, Prototypical Information Bottlenecking and Disentangling (PIBD), consisting of Prototypical Information Bottleneck (PIB) module for intra-modal redundancy and Prototypical Information Disentanglement (PID) module for inter-modal redundancy. Specifically, a variant of information bottleneck, PIB, is proposed to model prototypes approximating a bunch of instances for different risk levels, which can be used for selection of discriminative instances within modality. PID module decouples entangled multimodal data into compact distinct components: modality-common and modality-specific knowledge, under the guidance of the joint prototypical distribution. Extensive experiments on five cancer benchmark datasets demonstrated our superiority over other methods. The code is released. © 2024 12th International Conference on Learning Representations, ICLR 2024. 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(2024) Megjelent: 12th International Conference on Learning Representations, ICLR 2024<div class="BookChapter Publication long-list"> <div class="authors"> <img title="Idézőközlemény" style="float: left" src="/frontend/resources/grid/publication-citation-icon.png"> <div class="autype autype0"> <span class="author-name" >Zhang Y. </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Xu Y. </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Chen J. </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Xie F. ✉ </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Chen H. ✉ </span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;35778536" target="_blank">PROTOTYPICAL INFORMATION BOTTLENECKING AND DISENTANGLING FOR MULTIMODAL CANCER SURVIVAL PREDICTION</a></div> <div class="InBook"><div class="chapter-in">In:</div> <div class="authors"> </div> <div class="booktitle"><a href="/gui2/?mode=browse&params=publication;35178194" target="_blank">12th International Conference on Learning Representations, ICLR 2024 </a></div> <div class="conference"> Konferencia helye, ideje: <span class="conference-date">2024.05.07. - 2024.05.11.</span> </div> : <span class="publishers">International Conference on Learning Representations, ICLR</span>, <span class="page"> Paper Code 200372. </span> <span class="year">(2024)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:black" title="85199363043" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85199363043"> Scopus </a> </span> </span> <span class="bookchapter-ids">Befoglaló link(ek):</span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="https://openreview.net/group?id=ICLR.cc/2024/Conference#tab-accept-oral" target="_blank" href="https://openreview.net/group?id=ICLR.cc/2024/Conference#tab-accept-oral"> Egyéb URL </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="https://iclr.cc/Conferences/2024" target="_blank" href="https://iclr.cc/Conferences/2024"> Egyéb URL </a> </span> </span> <div class="publication-citation"> <a target="_blank" href="/api/publication?cond=citations.related;eq;35778536&sort=publishedYear,desc&sort=title"> Idézett közlemények száma: 1 </a> </div> <div class="mtid"><span class="long-pub-mtid">Közlemény: 35778536</span> | <span class="status-data status-APPROVED"> Nyilvános </span> <span class="long-book-mtid">Befoglaló: 35178194</span> Idéző Duplumgyanú | <span class="type-subtype">Egyéb konferenciaközlemény ( Konferenciaközlemény ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData">Scopus</span> </div> <div class="duplumMark">Duplumjelölés: 2025.02.21. 14:49 (Győrffy Balázs (Onkológia)) </div> <div class="lastModified">Utolsó módosítás: 2025.02.21. 14:49 Sonnevend Kinga (SE_AOK_Adm5_Élet_kutcsop, admin) </div> <pre class="comment" style="margin-top: 0; margin-bottom: 0;"><u>Megjegyzés</u>: The Hong Kong University of Science and Technology, Hong Kong Beihang University, China Conference code: 200372 Cited By :6 Export Date: 21 February 2025 Correspondence Address: Xie, F.; Beihang UniversityChina; email: xfy_73@buaa.edu.cn Correspondence ...</pre> </div> </div>