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2002.03704
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Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations
10 February 2020
Sebastian Farquhar
Lewis Smith
Y. Gal
UQCV
BDL
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Papers citing
"Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations"
4 / 4 papers shown
Using AI Uncertainty Quantification to Improve Human Decision-Making
International Conference on Machine Learning (ICML), 2023
L. Marusich
J. Bakdash
Yan Zhou
Murat Kantarcioglu
392
12
0
19 Sep 2023
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
BDL
UQCV
OOD
676
1,653
0
07 Jul 2021
Explicit Regularisation in Gaussian Noise Injections
Neural Information Processing Systems (NeurIPS), 2020
A. Camuto
M. Willetts
Umut Simsekli
Stephen J. Roberts
Chris Holmes
554
79
0
14 Jul 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian W. Ober
Laurence Aitchison
BDL
684
64
0
17 May 2020
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