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An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width
  Bayesian Neural Networks

An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks

16 November 2022
Jiayu Yao
Yaniv Yacoby
Beau Coker
Weiwei Pan
Finale Doshi-Velez
ArXivPDFHTML

Papers citing "An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks"

3 / 3 papers shown
Title
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Sanae Lotfi
Pavel Izmailov
Gregory W. Benton
Micah Goldblum
A. Wilson
UQCV
BDL
45
55
0
23 Feb 2022
Wide Mean-Field Bayesian Neural Networks Ignore the Data
Wide Mean-Field Bayesian Neural Networks Ignore the Data
Beau Coker
W. Bruinsma
David R. Burt
Weiwei Pan
Finale Doshi-Velez
UQCV
BDL
29
21
0
23 Feb 2022
Why bigger is not always better: on finite and infinite neural networks
Why bigger is not always better: on finite and infinite neural networks
Laurence Aitchison
173
51
0
17 Oct 2019
1