Priors in Bayesian Deep Learning: A Review

14 May 2021

Papers citing "Priors in Bayesian Deep Learning: A Review"

33 / 83 papers shown

Title
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study Tom Huix Szymon Majewski Alain Durmus Eric Moulines Anna Korba BDL 8 6 0 08 Jul 2022
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach Vishnu Raj Tianyu Cui Markus Heinonen Pekka Marttinen UQCV BDL 23 1 0 04 Jul 2022
Eliciting and Learning with Soft Labels from Every Annotator K. M. Collins Umang Bhatt Adrian Weller 11 44 0 02 Jul 2022
Gaussian Pre-Activations in Neural Networks: Myth or Reality? Pierre Wolinski Julyan Arbel AI4CE 65 8 0 24 May 2022
Simple Regularisation for Uncertainty-Aware Knowledge Distillation Martin Ferianc Miguel R. D. Rodrigues UQCV 32 0 0 19 May 2022
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility Hoileong Lee Fadhel Ayed Paul Jung Juho Lee Hongseok Yang François Caron 25 10 0 17 May 2022
Augmenting Neural Networks with Priors on Function Values Hunter Nisonoff Yixin Wang Jennifer Listgarten 13 3 0 10 Feb 2022
Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations Yuning You Tianlong Chen Zhangyang Wang Yang Shen SSL 11 59 0 04 Jan 2022
On out-of-distribution detection with Bayesian neural networks Francesco DÁngelo Christian Henning BDL UQCV 21 6 0 12 Oct 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 16 9 0 08 Oct 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin Mark Collier F. Wenzel J. Allingham J. Liu Dustin Tran Balaji Lakshminarayanan Jesse Berent Rodolphe Jenatton E. Kokiopoulou UQCV 21 11 0 06 Oct 2021
Neural Variational Gradient Descent L. Langosco Vincent Fortuin Heiko Strathmann BDL 17 19 0 22 Jul 2021
A Bayesian Approach to Invariant Deep Neural Networks Nikolaos Mourdoukoutas Marco Federici G. Pantalos Mark van der Wilk Vincent Fortuin BDL UQCV 16 0 0 20 Jul 2021
Hybrid Bayesian Neural Networks with Functional Probabilistic Layers Daniel T. Chang BDL UQCV 11 0 0 14 Jul 2021
Dangers of Bayesian Model Averaging under Covariate Shift Pavel Izmailov Patrick K. Nicholson Sanae Lotfi A. Wilson OOD UQCV BDL 13 45 0 22 Jun 2021
Bayesian Neural Networks: Essentials Daniel T. Chang UQCV BDL 14 12 0 22 Jun 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 25 93 0 22 Jun 2021
On Stein Variational Neural Network Ensembles Francesco DÁngelo Vincent Fortuin F. Wenzel UQCV BDL 15 25 0 20 Jun 2021
Data augmentation in Bayesian neural networks and the cold posterior effect Seth Nabarro Stoil Ganev Adrià Garriga-Alonso Vincent Fortuin Mark van der Wilk Laurence Aitchison BDL 6 37 0 10 Jun 2021
Probabilistic Deep Learning with Probabilistic Neural Networks and Deep Probabilistic Models Daniel T. Chang UD BDL UQCV 13 5 0 31 May 2021
Greedy Bayesian Posterior Approximation with Deep Ensembles A. Tiulpin Matthew B. Blaschko UQCV FedML 20 4 0 29 May 2021
Revisiting Bayesian Autoencoders with MCMC Rohitash Chandra Mahir Jain Manavendra Maharana P. Krivitsky UQCV BDL 19 17 0 13 Apr 2021
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction Dominik Narnhofer Alexander Effland Erich Kobler Kerstin Hammernik Florian Knoll T. Pock UQCV BDL 15 48 0 12 Feb 2021
Bayesian Neural Network Priors Revisited Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard E. Turner Mark van der Wilk Laurence Aitchison BDL UQCV 43 136 0 12 Feb 2021
Inductive Biases for Deep Learning of Higher-Level Cognition Anirudh Goyal Yoshua Bengio AI4CE 13 343 0 30 Nov 2020
Sparse Gaussian Process Variational Autoencoders Matthew Ashman Jonathan So Will Tebbutt Vincent Fortuin Michael Pearce Richard E. Turner 16 33 0 20 Oct 2020
PAC $^m$ -Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime Warren Morningstar Alexander A. Alemi Joshua V. Dillon 74 16 0 19 Oct 2020
Informative Bayesian Neural Network Priors for Weak Signals Tianyu Cui A. Havulinna Pekka Marttinen Samuel Kaski 24 9 0 24 Feb 2020
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 188 495 0 11 Jun 2018
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 165 664 0 07 Jun 2018
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 60 171 0 08 Jul 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 84 271 0 24 Feb 2014