{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T13:20:24Z","timestamp":1768310424231,"version":"3.49.0"},"reference-count":31,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T00:00:00Z","timestamp":1765238400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T00:00:00Z","timestamp":1765238400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000006","name":"Office of Naval Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,9]]},"DOI":"10.1109\/cdc57313.2025.11312278","type":"proceedings-article","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T18:19:56Z","timestamp":1768241996000},"page":"198-205","source":"Crossref","is-referenced-by-count":0,"title":["Kalman Bayesian Transformer"],"prefix":"10.1109","author":[{"given":"Haoming","family":"Jing","sequence":"first","affiliation":[{"name":"Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,Pennsylvania,United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oren","family":"Wright","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,Pennsylvania,United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 M. F.","family":"Moura","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,Pennsylvania,United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yorie","family":"Nakahira","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,Pennsylvania,United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Parameter-efficient fine-tuning for large models: A comprehensive survey","author":"Han","year":"2024"},{"key":"ref2","first-page":"65317","article-title":"Bayestune: Bayesian sparse deep model fine-tuning","volume-title":"Advances in Neural Information Processing Systems","volume":"36","author":"Kim","year":"2023"},{"key":"ref3","article-title":"Bayesian active learning with pretrained language models","author":"Margatina","year":"2021","journal-title":"CoRR"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.52202\/079017-2164"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.5555\/2986459.2986721"},{"issue":"1","key":"ref6","first-page":"1303","article-title":"Stochastic variational inference","volume":"14","author":"Hoffman","year":"2013","journal-title":"the Journal of machine Learning research"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1063\/1.1699114"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1984.4767596"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-0745-0"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2020.1847120"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i8.26200"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9414046"},{"key":"ref13","article-title":"Bayesformer: Transformer with uncertainty estimation","author":"Sankararaman","year":"2022"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1162\/089976699300016872"},{"key":"ref15","first-page":"33","article-title":"Tractable inference for complex stochastic processes","volume-title":"Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, UAI\u201998, (San Francisco, CA, USA)","author":"Boyen"},{"key":"ref16","first-page":"AAI0803033","article-title":"A Family of Algorithms for Approximate Bayesian Inference","volume-title":"PhD thesis, Massachusetts Institute of Technology, USA","author":"Minka","year":"2001"},{"key":"ref17","article-title":"Deterministic variational inference for robust Bayesian neural networks","volume-title":"International Conference on Learning Representations","author":"Wu"},{"key":"ref18","first-page":"4087","article-title":"An analytic solution to covariance propagation in neural networks","volume-title":"International Conference on Artificial Intelligence and Statistics","author":"Wright"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00355"},{"key":"ref20","first-page":"1861","article-title":"Probabilistic backpropagation for scalable learning of Bayesian neural networks","volume-title":"Proceedings of the 32nd International Conference on International Conference on Machine Learning - Volume 37, ICML\u201915","author":"Hern\u00e1ndez-Lobato"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10296"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1992.4.3.448"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295309"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-05946-3"},{"key":"ref25","first-page":"4629","article-title":"What are bayesian neural network posteriors really like?","volume-title":"International conference on machine learning","author":"Izmailov"},{"key":"ref26","first-page":"344","article-title":"Learnable uncertainty under laplace approximations","author":"Kristiadi","year":"2021","journal-title":"Uncertainty in Artificial Intelligence"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1506.02142"},{"key":"ref28","first-page":"13153","article-title":"A simple baseline for Bayesian uncertainty in deep learning","volume-title":"Proceedings of the 33rd International Conference on Neural Information Processing Systems","author":"Maddox"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(92)90065-6"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3017292"}],"event":{"name":"2025 IEEE 64th Conference on Decision and Control (CDC)","location":"Rio de Janeiro, Brazil","start":{"date-parts":[[2025,12,9]]},"end":{"date-parts":[[2025,12,12]]}},"container-title":["2025 IEEE 64th Conference on Decision and Control (CDC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11311984\/11311968\/11312278.pdf?arnumber=11312278","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T08:13:50Z","timestamp":1768292030000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11312278\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,9]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/cdc57313.2025.11312278","relation":{},"subject":[],"published":{"date-parts":[[2025,12,9]]}}}