{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T10:09:26Z","timestamp":1730282966457,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"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":[[2019,10]]},"DOI":"10.1109\/mlsp.2019.8918767","type":"proceedings-article","created":{"date-parts":[[2019,12,6]],"date-time":"2019-12-06T08:23:52Z","timestamp":1575620632000},"page":"1-6","source":"Crossref","is-referenced-by-count":2,"title":["Asymptotics of Maximum Likelihood Parameter Estimates For Gaussian Processes: The Ornstein\u2013Uhlenbeck Prior"],"prefix":"10.1109","author":[{"given":"Toni","family":"Karvonen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Filip","family":"Tronarp","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simo","family":"Sarkka","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1216\/RMJ-1972-2-3-379"},{"key":"ref11","first-page":"55","article-title":"A new approach to maximum likelihood estimation for stochastic differential equations based on discrete observations","volume":"22","author":"pedersen","year":"1995","journal-title":"Scandinavian Journal of Statistics"},{"key":"ref12","article-title":"Gaussian Processes for Machine Learning","author":"rasmussen","year":"2006","journal-title":"Adaptive Computation and Machine Learning"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1177012413"},{"journal-title":"Stochastic Differential Equation","year":"2019","author":"s\u00e4rkk\u00e4","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2013.2246292"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10444-011-9192-5"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1214\/13-EJS798"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1214\/14-AOS1270"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-019-09900-1"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP.2010.5589113"},{"key":"ref3","article-title":"Can we trust Bayesian uncertainty quantification from Gaussian process priors with squared exponential covariance kernel?","author":"hadji","year":"2019","journal-title":"arXiv 1904 01383"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-75839-8"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.2015.0142"},{"key":"ref8","first-page":"5882","article-title":"A Bayes– Sard cubature method","volume":"31","author":"karvonen","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.31390\/cosa.5.1.08"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1137\/17M1139357"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1214\/18-STS660"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/BF01905932"},{"key":"ref20","first-page":"2095","article-title":"Information rates of nonparametric Gaussian process methods","volume":"12","author":"van der vaart","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1198\/016214505000000169"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1137\/15M105358X"}],"event":{"name":"2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP)","start":{"date-parts":[[2019,10,13]]},"location":"Pittsburgh, PA, USA","end":{"date-parts":[[2019,10,16]]}},"container-title":["2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8911118\/8918685\/08918767.pdf?arnumber=8918767","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T03:09:26Z","timestamp":1657854566000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8918767\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/mlsp.2019.8918767","relation":{},"subject":[],"published":{"date-parts":[[2019,10]]}}}