{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T04:39:29Z","timestamp":1792730369681,"version":"4.5.0"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/tdmrep.html"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62576214"],"award-info":[{"award-number":["62576214"]}]},{"name":"Guangdong Basic and Applied Basic Research Foundation","award":["2024B1515020109"],"award-info":[{"award-number":["2024B1515020109"]}]},{"name":"Hong Kong RGC General Research Fund","award":["GRF 13200425"],"award-info":[{"award-number":["GRF 13200425"]}]},{"name":"2025 Characteristics and Innovation Grant for College of Guangdong Province","award":["2025KTSCX152"],"award-info":[{"award-number":["2025KTSCX152"]}]},{"name":"Open Fund of Tianjin Key Laboratory of Brain-Inspired Intelligence Technology in 2026"},{"name":"Intelligent Computing Center of Shenzhen University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1109\/tcyb.2026.3717080","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T19:04:11Z","timestamp":1785870251000},"page":"6642-6655","source":"Crossref","is-referenced-by-count":0,"title":["MC-SNN: Multicenter Stochastic Neural Network for Adversarially Robust Learning"],"prefix":"10.1109","volume":"56","author":[{"given":"Meng","family":"Hu","sequence":"first","affiliation":[{"name":"Shenzhen University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2586-5604","authenticated-orcid":false,"given":"Ran","family":"Wang","sequence":"additional","affiliation":[{"name":"Shenzhen University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanting","family":"Guo","sequence":"additional","affiliation":[{"name":"Dongguan University of Technology","place":["Dongguan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6036-4728","authenticated-orcid":false,"given":"Xizhao","family":"Wang","sequence":"additional","affiliation":[{"name":"Shenzhen University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7484-7261","authenticated-orcid":false,"given":"Sam","family":"Kwong","sequence":"additional","affiliation":[{"name":"Lingnan University","place":["Hong Kong, SAR, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.06083"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2933223"},{"key":"ref3","first-page":"7472","article-title":"Theoretically principled trade-off between robustness and accuracy","volume-title":"Proc. IEEE\/CVF Int. Conf. Comput. Vis.","author":"Zhang"},{"key":"ref4","article-title":"Improving adversarial robustness requires revisiting misclassified examples","volume-title":"Proc. 8th Int. Conf. Learn. Represent. (ICLR)","author":"Wang"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2025.112840"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1049\/cit2.70121"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1049\/csy2.12117"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3449908"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2020.2991774"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2024.3475034"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3009953"},{"key":"ref12","article-title":"Deep variational information bottleneck","volume-title":"Proc. 5th Int. Conf. Learn. Represent.","author":"Alemi"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.12.041"},{"key":"ref14","first-page":"3047","article-title":"Weight-covariance alignment for adversarially robust neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Eustratiadis"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICME55011.2023.00392"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICME55011.2023.00305"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i4.16436"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM51629.2021.00186"},{"key":"ref19","first-page":"1613","article-title":"Weight uncertainty in neural network","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Blundell"},{"key":"ref20","article-title":"Adv-BNN: Improved adversarial defense through robust Bayesian neural network","volume-title":"Proc. 7th Int. Conf. Learn. Represent.","author":"Liu"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00068"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00132"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3169217"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2023.103855"},{"key":"ref25","article-title":"Explaining and harnessing adversarial examples","volume-title":"Proc. 3rd Int. Conf. Learn. Represent.","author":"Goodfellow"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/694"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00957"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref29","article-title":"Minimally distorted adversarial examples with a fast adaptive boundary attack","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Croce"},{"key":"ref30","first-page":"2206","article-title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Croce"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01468"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2025.3608261"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2025.3548175"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2025.3621901"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3366349"},{"key":"ref36","first-page":"16049","article-title":"How does information bottleneck help deep learning","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","volume":"202","author":"Kawaguchi"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3329525"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3510627"},{"key":"ref39","article-title":"The information bottleneck method","author":"Tishby","year":"2000","journal-title":"arxiv: physics\/0004057"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00575"},{"key":"ref41","volume-title":"Foundations of Machine Learning","author":"Mehryar","year":"2012"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2025.3567014"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00020"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20065-6_18"},{"key":"ref45","article-title":"Averaging weights leads to wider optima and better generalization","author":"Izmailov","year":"2018","journal-title":"arXiv:1803.05407"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00348"},{"key":"ref47","article-title":"Adversarial weight perturbation helps robust generalization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wu"},{"key":"ref48","first-page":"23258","article-title":"Probabilistic margins for instance reweighting in adversarial training","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref49","first-page":"25595","article-title":"Understanding robust overfitting of adversarial training and beyond","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yu"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00408"},{"key":"ref51","first-page":"59024","article-title":"On the duality between sharpness-aware minimization and adversarial training","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"235","author":"Zhang"},{"key":"ref52","first-page":"36246","article-title":"Better diffusion models further improve adversarial training","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Wang"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2024.3380437"},{"key":"ref54","article-title":"Fast is better than free: Revisiting adversarial training","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Wong"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19772-7_33"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73390-1_9"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6221036\/11746051\/11641266.pdf?arnumber=11641266","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T04:26:32Z","timestamp":1792729592000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11641266\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":56,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2026.3717080","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,11]]}}}