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Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight
  Posterior Approximations
v1v2v3v4 (latest)

Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations

10 February 2020
Sebastian Farquhar
Lewis Smith
Y. Gal
    UQCVBDL
ArXiv (abs)PDFHTML

Papers citing "Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations"

3 / 3 papers shown
Title
A Survey of Uncertainty in Deep Neural Networks
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDLUQCVOOD
282
1,275
0
07 Jul 2021
Explicit Regularisation in Gaussian Noise Injections
Explicit Regularisation in Gaussian Noise Injections
A. Camuto
M. Willetts
Umut Simsekli
Stephen J. Roberts
Chris Holmes
146
63
0
14 Jul 2020
Global inducing point variational posteriors for Bayesian neural
  networks and deep Gaussian processes
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian W. Ober
Laurence Aitchison
BDL
178
61
0
17 May 2020
1