{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T16:50:16Z","timestamp":1783183816870,"version":"3.54.6"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council through the Discovery Project","doi-asserted-by":"publisher","award":["DP200100700"],"award-info":[{"award-number":["DP200100700"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"name":"International Research Training Program Scholarship (IRTP) of Australia"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1109\/tcyb.2022.3191022","type":"journal-article","created":{"date-parts":[[2022,8,9]],"date-time":"2022-08-09T20:36:46Z","timestamp":1660077406000},"page":"962-973","source":"Crossref","is-referenced-by-count":13,"title":["Robust Gaussian Process Regression With Input Uncertainty: A PAC-Bayes Perspective"],"prefix":"10.1109","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8107-8587","authenticated-orcid":false,"given":"Tianyu","family":"Liu","sequence":"first","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0690-4732","authenticated-orcid":false,"given":"Jie","family":"Lu","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3368-2100","authenticated-orcid":false,"given":"Zheng","family":"Yan","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3960-0583","authenticated-orcid":false,"given":"Guangquan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2008.923118"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-00144-6"},{"key":"ref3","first-page":"6055","article-title":"Gaussian process-based real-time learning for safety critical applications","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lederer"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2019.09.145"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3120188"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3070434"},{"issue":"36","key":"ref7","first-page":"1","article-title":"Multi-class Gaussian process classification with noisy inputs","volume":"22","author":"Villacampa-Calvo","year":"2021","journal-title":"J. Mach. Learn. Res."},{"key":"ref8","first-page":"1341","article-title":"Gaussian process training with input noise","volume-title":"Advances in Neural Information Processing Systems","volume":"24","author":"McHutchon","year":"2011"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/279943.279989"},{"key":"ref10","article-title":"PAC-Bayesian theory meets Bayesian inference","author":"Germain","year":"2016","journal-title":"arXiv:1605.08636"},{"issue":"1","key":"ref11","first-page":"8374","article-title":"On the properties of variational approximations of Gibbs posteriors","volume":"17","author":"Alquier","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"ref12","article-title":"PAC-Bayes unleashed: Generalisation bounds with unbounded losses","author":"Haddouche","year":"2020","journal-title":"arXiv:2006.07279"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2012.10.013"},{"key":"ref14","first-page":"9214","article-title":"PAC-Bayes bounds for stable algorithms with instance-dependent priors","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Rivasplata","year":"2018"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-16108-7_13"},{"key":"ref16","first-page":"8430","article-title":"Data-dependent PAC-Bayes priors via differential privacy","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Dziugaite","year":"2018"},{"key":"ref17","article-title":"Sparse Gaussian processes using pseudo-inputs","volume-title":"Advances in Neural Information Processing Systems","volume":"18","author":"Snelson","year":"2005"},{"key":"ref18","first-page":"567","article-title":"Variational learning of inducing variables in sparse Gaussian processes","volume-title":"Proc. Artif. Intell. Stat.","author":"Titsias"},{"key":"ref19","first-page":"282","article-title":"Gaussian processes for big data","volume-title":"Proc. 29th Conf. Uncertainty Artif. Intell.","author":"Hensman"},{"key":"ref20","article-title":"Convergence of sparse variational inference in Gaussian processes regression","author":"Burt","year":"2020","journal-title":"arXiv:2008.00323"},{"key":"ref21","article-title":"Fast Gaussian process regression using KD-trees","volume-title":"Advances in Neural Information Processing Systems","volume":"18","author":"Shen","year":"2005"},{"key":"ref22","article-title":"Automatic online tuning for fast Gaussian summation","volume-title":"Advances in Neural Information Processing Systems","volume":"21","author":"Morariu","year":"2008"},{"key":"ref23","first-page":"1775","article-title":"Kernel interpolation for scalable structured Gaussian processes (KISS-GP)","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Wilson"},{"key":"ref24","first-page":"2874","article-title":"Doubly sparse variational Gaussian processes","volume-title":"Proc. Int. Conf. Artif. Intell. Stat.","author":"Adam"},{"key":"ref25","article-title":"Dual parameterization of sparse variational Gaussian processes","volume-title":"Advances in Neural Information Processing Systems","volume":"34","author":"Adam","year":"2021"},{"key":"ref26","article-title":"Gaussian process for noisy inputs with ordering constraints","author":"Tran","year":"2015","journal-title":"arXiv:1507.00052"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-28650-9_4"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2019.2921476"},{"key":"ref29","first-page":"280","article-title":"Robust multi-class Gaussian process classification","volume-title":"Advances in Neural Information Processing Systems","volume":"24","author":"Hern\u00e1ndez-Lobato","year":"2011"},{"key":"ref30","first-page":"3550","article-title":"Scalable multi-class Gaussian process classification using expectation propagation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Villacampa-Calvo"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1162\/153244303765208386"},{"key":"ref32","article-title":"Learning Gaussian processes by minimizing PAC-Bayesian generalization bounds","author":"Reeb","year":"2018","journal-title":"arXiv:1810.12263"},{"key":"ref33","article-title":"Derivative observations in Gaussian process models of dynamic systems","volume-title":"Advances in Neural Information Processing Systems","author":"Solak","year":"2003"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.5555\/1046920.1194909"},{"key":"ref35","first-page":"351","article-title":"Scalable variational Gaussian process classification","volume-title":"Proc. Artif. Intell. Stat.","author":"Hensman"},{"key":"ref36","article-title":"GPyTorch: Blackbox matrix-matrix Gaussian process inference with GPU acceleration","volume-title":"Advances in Neural Information Processing Systems","author":"Gardner","year":"2018"},{"key":"ref37","article-title":"Gaussian process priors with uncertain inputs? Application to multiple-step ahead time series forecasting","volume-title":"Advances in Neural Information Processing Systems","volume":"16","author":"Girard","year":"2003"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/10402573\/09852982.pdf?arnumber=9852982","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T18:55:10Z","timestamp":1732906510000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9852982\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2]]},"references-count":37,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2022.3191022","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2]]}}}