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How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences
Kasprzak, Mikolaj
;
Giordano, Ryan
;
Broderick, Tamara
2022
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https://hdl.handle.net/10993/53906
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2209.14992.pdf
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Disciplines :
Mathematics
Author, co-author :
Kasprzak, Mikolaj
;
University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH)
Giordano, Ryan;
Massachusetts Institute of Technology - MIT
Broderick, Tamara;
Massachusetts Institute of Technology - MIT
Language :
English
Title :
How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences
Publication date :
2022
Source :
https://arxiv.org/abs/2209.14992
Funders :
CE - Commission Européenne [BE]
Available on ORBilu :
since 17 January 2023
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