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Overpruning in Variational Bayesian Neural Networks

Overpruning in Variational Bayesian Neural Networks

18 January 2018
Brian L. Trippe
Richard Turner
    BDL
ArXivPDFHTML

Papers citing "Overpruning in Variational Bayesian Neural Networks"

15 / 15 papers shown
Title
Variational Visual Question Answering
Variational Visual Question Answering
Tobias Jan Wieczorek
Nathalie Daun
Mohammad Emtiyaz Khan
Marcus Rohrbach
OOD
44
0
0
14 May 2025
Temporal-Difference Variational Continual Learning
Temporal-Difference Variational Continual Learning
Luckeciano C. Melo
Alessandro Abate
Yarin Gal
BDL
CLL
VLM
49
0
0
10 Oct 2024
RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit
  Neural Representations
RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations
Carlos Rombaldo Junior
Ingolf Becker
Zongyu Guo
Shane Johnson
13
12
0
29 Sep 2023
Do Bayesian Neural Networks Need To Be Fully Stochastic?
Do Bayesian Neural Networks Need To Be Fully Stochastic?
Mrinank Sharma
Sebastian Farquhar
Eric T. Nalisnick
Tom Rainforth
BDL
23
52
0
11 Nov 2022
Markov Chain Score Ascent: A Unifying Framework of Variational Inference
  with Markovian Gradients
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients
Kyurae Kim
Jisu Oh
Jacob R. Gardner
Adji Bousso Dieng
Hongseok Kim
BDL
37
8
0
13 Jun 2022
Partitioned Variational Inference: A Framework for Probabilistic
  Federated Learning
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
19
12
0
24 Feb 2022
TyXe: Pyro-based Bayesian neural nets for Pytorch
TyXe: Pyro-based Bayesian neural nets for Pytorch
H. Ritter
Theofanis Karaletsos
OOD
MU
BDL
34
6
0
01 Oct 2021
Generalized Variational Continual Learning
Generalized Variational Continual Learning
Noel Loo
S. Swaroop
Richard Turner
BDL
CLL
33
58
0
24 Nov 2020
Depth Uncertainty in Neural Networks
Depth Uncertainty in Neural Networks
Javier Antorán
J. Allingham
José Miguel Hernández-Lobato
UQCV
OOD
BDL
46
100
0
15 Jun 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
26
60
0
17 May 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
Theofanis Karaletsos
T. Bui
BDL
20
23
0
10 Feb 2020
Bayesian Deep Net GLM and GLMM
Bayesian Deep Net GLM and GLMM
Minh-Ngoc Tran
Nghia Nguyen
David J. Nott
Robert Kohn
BDL
17
73
0
25 May 2018
Meta-Learning Probabilistic Inference For Prediction
Meta-Learning Probabilistic Inference For Prediction
Jonathan Gordon
J. Bronskill
Matthias Bauer
Sebastian Nowozin
Richard Turner
BDL
45
263
0
24 May 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,695
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,167
0
06 Jun 2015
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