{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T05:21:14Z","timestamp":1737091274344,"version":"3.33.0"},"reference-count":19,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T00:00:00Z","timestamp":1694908800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T00:00:00Z","timestamp":1694908800000},"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":[[2023,9,17]]},"DOI":"10.1109\/mlsp55844.2023.10286005","type":"proceedings-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T17:55:41Z","timestamp":1698083741000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["Layer Ensembles"],"prefix":"10.1109","author":[{"given":"Illia","family":"Oleksiienko","sequence":"first","affiliation":[{"name":"Aarhus University,Department of Electrical and Computer Engineering,Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandros","family":"Iosifidis","sequence":"additional","affiliation":[{"name":"Aarhus University,Department of Electrical and Computer Engineering,Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","article-title":"Auto-encoding variational bayes","volume":"2","author":"kingma","year":"2014","journal-title":"ICLRE"},{"key":"ref12","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"JMLR"},{"key":"ref15","article-title":"Deep sub-ensembles for fast uncertainty estimation in image classification","author":"valdenegro-toro","year":"2019","journal-title":"arXiv 1910 08168"},{"key":"ref14","article-title":"Variational neural networks","author":"oleksiienko","year":"2022","journal-title":"arxiv 2207 01524"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref10","article-title":"Deep neural networks as gaussian processes","author":"lee","year":"2018","journal-title":"ICLRE"},{"key":"ref2","article-title":"Bayesian Deep Learning and a Probabilistic Perspective of Generalization","volume":"33","author":"wilson","year":"2020","journal-title":"NeurIPS"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1088\/0954-898X\/6\/3\/011"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16452-1_49"},{"key":"ref16","article-title":"Batchensemble: An alternative approach to efficient ensemble and lifelong learning","volume":"8","author":"wen","year":"2020","journal-title":"ICLRE"},{"article-title":"Github code for epistemic neural networks","year":"2021","author":"osband","key":"ref19"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3850\/9783981537079_0819"},{"key":"ref8","first-page":"8626","article-title":"Randomized prior functions for deep reinforcement learning","volume":"31","author":"osband","year":"2018","journal-title":"NeurIPS"},{"key":"ref7","first-page":"1050","article-title":"Dropout as a bayesian approximation: Representing model uncertainty in deep learning","volume":"48","author":"gal","year":"2016","journal-title":"ICML"},{"key":"ref9","article-title":"Epistemic Neural Networks","author":"osband","year":"2021","journal-title":"arXiv 2107 08924"},{"key":"ref4","article-title":"Bayesian learning for neural networks: an algorithmic survey","author":"magris","year":"2022","journal-title":"arxiv 2211 11865"},{"key":"ref3","article-title":"Bayesian neural networks","author":"charnock","year":"2020","journal-title":"arXiv 2006 01490"},{"key":"ref6","article-title":"Hypermodels for exploration","volume":"8","author":"dwaracherla","year":"2020","journal-title":"ICLRE"},{"key":"ref5","first-page":"1613","article-title":"Weight Uncertainty in Neural Networks","volume":"37","author":"blundell","year":"2015","journal-title":"ICML"}],"event":{"name":"2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)","start":{"date-parts":[[2023,9,17]]},"location":"Rome, Italy","end":{"date-parts":[[2023,9,20]]}},"container-title":["2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10285838\/10285858\/10286005.pdf?arnumber=10286005","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T18:30:43Z","timestamp":1737052243000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10286005\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,17]]},"references-count":19,"URL":"https:\/\/doi.org\/10.1109\/mlsp55844.2023.10286005","relation":{},"subject":[],"published":{"date-parts":[[2023,9,17]]}}}