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1801.06230
Cited By
Overpruning in Variational Bayesian Neural Networks
18 January 2018
Brian L. Trippe
Richard Turner
BDL
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Papers citing
"Overpruning in Variational Bayesian Neural Networks"
31 / 31 papers shown
Variational Visual Question Answering for Uncertainty-Aware Selective Prediction
Tobias Jan Wieczorek
Nathalie Daun
Mohammad Emtiyaz Khan
Marcus Rohrbach
OOD
570
0
0
14 May 2025
Understanding the Trade-offs in Accuracy and Uncertainty Quantification: Architecture and Inference Choices in Bayesian Neural Networks
Alisa Sheinkman
Sara Wade
UQCV
BDL
373
0
0
14 Mar 2025
Temporal-Difference Variational Continual Learning
Luckeciano C. Melo
Alessandro Abate
Yarin Gal
BDL
CLL
VLM
603
0
0
10 Oct 2024
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery
Neural Information Processing Systems (NeurIPS), 2023
Yashas Annadani
Nick Pawlowski
Joel Jennings
Stefan Bauer
Cheng Zhang
Wenbo Gong
CML
BDL
337
31
0
26 Jul 2023
Density Uncertainty Layers for Reliable Uncertainty Estimation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Yookoon Park
David M. Blei
UQCV
BDL
199
6
0
21 Jun 2023
Do Bayesian Neural Networks Need To Be Fully Stochastic?
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Mrinank Sharma
Sebastian Farquhar
Eric T. Nalisnick
Tom Rainforth
BDL
273
70
0
11 Nov 2022
On the detrimental effect of invariances in the likelihood for variational inference
Neural Information Processing Systems (NeurIPS), 2022
Richard Kurle
R. Herbrich
Tim Januschowski
Bernie Wang
Jan Gasthaus
294
9
0
15 Sep 2022
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients
Neural Information Processing Systems (NeurIPS), 2022
Kyurae Kim
Jisu Oh
Jacob R. Gardner
Adji Bousso Dieng
Hongseok Kim
BDL
332
9
0
13 Jun 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning
Matthew Ashman
T. Bui
Cuong V Nguyen
Efstratios Markou
Adrian Weller
S. Swaroop
Richard Turner
FedML
364
15
0
24 Feb 2022
Wide Mean-Field Bayesian Neural Networks Ignore the Data
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Beau Coker
W. Bruinsma
David R. Burt
Weiwei Pan
Finale Doshi-Velez
UQCV
BDL
164
24
0
23 Feb 2022
Enhancing variational generation through self-decomposition
IEEE Access (IEEE Access), 2022
Andrea Asperti
Laura Bugo
Daniele Filippini
DRL
217
2
0
06 Feb 2022
TyXe: Pyro-based Bayesian neural nets for Pytorch
H. Ritter
Theofanis Karaletsos
OOD
MU
BDL
198
7
0
01 Oct 2021
Wide Mean-Field Variational Bayesian Neural Networks Ignore the Data
Beau Coker
Weiwei Pan
Finale Doshi-Velez
BDL
104
10
0
13 Jun 2021
A survey on Variational Autoencoders from a GreenAI perspective
SN Computer Science (SN Comput. Sci.), 2021
Andrea Asperti
David Evangelista
E. Loli Piccolomini
DRL
190
68
0
01 Mar 2021
Bayesian Neural Network Priors Revisited
International Conference on Learning Representations (ICLR), 2021
Vincent Fortuin
Adrià Garriga-Alonso
Sebastian W. Ober
F. Wenzel
Gunnar Rätsch
Richard Turner
Mark van der Wilk
Laurence Aitchison
BDL
UQCV
378
155
0
12 Feb 2021
Generalized Variational Continual Learning
International Conference on Learning Representations (ICLR), 2020
Noel Loo
S. Swaroop
Richard Turner
BDL
CLL
215
70
0
24 Nov 2020
Task Agnostic Continual Learning Using Online Variational Bayes with Fixed-Point Updates
Neural Computation (Neural Comput.), 2020
Chen Zeno
Itay Golan
Elad Hoffer
Daniel Soudry
OOD
FedML
265
48
0
01 Oct 2020
Bayesian neural networks and dimensionality reduction
Deborshee Sen
Theodore Papamarkou
David B. Dunson
BDL
260
5
0
18 Aug 2020
Depth Uncertainty in Neural Networks
Javier Antorán
J. Allingham
José Miguel Hernández-Lobato
UQCV
OOD
BDL
407
113
0
15 Jun 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian W. Ober
Laurence Aitchison
BDL
610
62
0
17 May 2020
Addressing Catastrophic Forgetting in Few-Shot Problems
International Conference on Machine Learning (ICML), 2020
Pauching Yap
H. Ritter
David Barber
CLL
BDL
347
20
0
30 Apr 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
Neural Information Processing Systems (NeurIPS), 2020
Theofanis Karaletsos
T. Bui
BDL
210
27
0
10 Feb 2020
Ín-Between' Uncertainty in Bayesian Neural Networks
Andrew Y. K. Foong
Yingzhen Li
José Miguel Hernández-Lobato
Richard Turner
BDL
UQCV
199
131
0
27 Jun 2019
Improving and Understanding Variational Continual Learning
S. Swaroop
Cuong V Nguyen
T. Bui
Richard Turner
CLL
128
53
0
06 May 2019
Function Space Particle Optimization for Bayesian Neural Networks
International Conference on Learning Representations (ICLR), 2019
Ziyu Wang
Zhaolin Ren
Jun Zhu
Bo Zhang
BDL
192
68
0
26 Feb 2019
Gaussian Mean Field Regularizes by Limiting Learned Information
Entropy (Entropy), 2019
Julius Kunze
Louis Kirsch
H. Ritter
David Barber
FedML
MLT
157
2
0
12 Feb 2019
Variational Bayesian Dropout with a Hierarchical Prior
Computer Vision and Pattern Recognition (CVPR), 2018
Yuhang Liu
Wenyong Dong
Lei Zhang
Dong Gong
Javen Qinfeng Shi
BDL
153
20
0
19 Nov 2018
Doubly Semi-Implicit Variational Inference
Dmitry Molchanov
V. Kharitonov
Artem Sobolev
Dmitry Vetrov
BDL
263
41
0
05 Oct 2018
Bayesian Deep Net GLM and GLMM
Minh-Ngoc Tran
Nghia Nguyen
David J. Nott
Robert Kohn
BDL
370
77
0
25 May 2018
Meta-Learning Probabilistic Inference For Prediction
Jonathan Gordon
J. Bronskill
Matthias Bauer
Sebastian Nowozin
Richard Turner
BDL
489
281
0
24 May 2018
Conditional Density Estimation with Bayesian Normalising Flows
Brian L. Trippe
Richard Turner
BDL
188
92
0
14 Feb 2018
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