{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T19:20:47Z","timestamp":1776885647627,"version":"3.51.2"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T00:00:00Z","timestamp":1733184000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T00:00:00Z","timestamp":1733184000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,3]]},"DOI":"10.1109\/apsipaasc63619.2025.10849018","type":"proceedings-article","created":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T18:37:05Z","timestamp":1738003025000},"page":"1-5","source":"Crossref","is-referenced-by-count":2,"title":["A Joint Graph Signal and Laplacian Denoising Network"],"prefix":"10.1109","author":[{"given":"Zepeng","family":"Zhang","sequence":"first","affiliation":[{"name":"&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne,Lausanne,Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziping","family":"Zhao","sequence":"additional","affiliation":[{"name":"ShanghaiTech University,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-16-6054-2"},{"key":"ref2","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"International Conference on Learning Representations","author":"Kipf"},{"key":"ref3","article-title":"Inductive representation learning on large graphs","volume":"30","author":"Hamilton","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482225"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449953"},{"key":"ref6","article-title":"Towards understanding graph neural networks: An algorithm unrolling perspective","author":"Zhang","year":"2022"},{"key":"ref7","article-title":"Predict then propagate: Graph neural networks meet personalized pagerank","volume-title":"International Conference on Learning Representations","author":"Gasteiger"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220078"},{"key":"ref9","article-title":"Adversarial attacks on graph neural networks via meta learning","volume-title":"International Conference on Learning Representations","author":"Z\u00fcgner"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/669"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371789"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403049"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/SPCOM55316.2022.9840814"},{"key":"ref14","first-page":"6837","article-title":"Elastic graph neural networks","volume-title":"International Conference on Machine Learning","author":"Liu"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2021.3087905"},{"key":"ref16","article-title":"ASGNN: Graph neural networks with adaptive structure","author":"Zhang","year":"2022"},{"issue":"22","key":"ref17","first-page":"1","article-title":"A unified framework for structured graph learning via spectral constraints","volume":"21","author":"Kumar","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref18","first-page":"641","article-title":"Learning social infectivity in sparse low-rank networks using multi-dimensional hawkes processes","volume-title":"Artificial Intelligence and Statistics","author":"Zhou","year":"2013"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/springerreference_5883"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2601299"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1137\/120891009"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v29i3.2157"},{"key":"ref23","article-title":"Deeprobust: A pytorch library for adversarial attacks and defenses","author":"Li","year":"2020"}],"event":{"name":"2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","location":"Macau, Macao","start":{"date-parts":[[2024,12,3]]},"end":{"date-parts":[[2024,12,6]]}},"container-title":["2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10848542\/10848533\/10849018.pdf?arnumber=10849018","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T06:24:01Z","timestamp":1738045441000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10849018\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,3]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/apsipaasc63619.2025.10849018","relation":{},"subject":[],"published":{"date-parts":[[2024,12,3]]}}}