Bayesian Neural Network Priors Revisited

12 February 2021

Papers citing "Bayesian Neural Network Priors Revisited"

21 / 21 papers shown

Title
BackSlash: Rate Constrained Optimized Training of Large Language Models Jun Wu Jiangtao Wen Yuxing Han 34 0 0 23 Apr 2025
Streamlining Prediction in Bayesian Deep Learning Rui Li Marcus Klasson Arno Solin Martin Trapp UQCV BDL 91 1 0 27 Nov 2024
Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction Jiayang Shi Junyi Zhu D. Pelt K. Batenburg Matthew B. Blaschko 24 3 0 03 May 2024
Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions Alberto Bordino Stefano Favaro S. Fortini 25 7 0 08 Apr 2023
Detection of Uncertainty in Exceedance of Threshold (DUET): An Adversarial Patch Localizer Terence Jie Chua Wen-li Yu Junfeng Zhao AAML UQCV 14 1 0 18 Mar 2023
Fixing Overconfidence in Dynamic Neural Networks Lassi Meronen Martin Trapp Andrea Pilzer Le Yang Arno Solin BDL 21 16 0 13 Feb 2023
MARS: Meta-Learning as Score Matching in the Function Space Krunoslav Lehman Pavasovic Jonas Rothfuss Andreas Krause BDL 8 4 0 24 Oct 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 21 5 0 22 Jun 2022
Large-width asymptotics for ReLU neural networks with $α$ -Stable initializations Stefano Favaro S. Fortini Stefano Peluchetti 15 2 0 16 Jun 2022
How Tempering Fixes Data Augmentation in Bayesian Neural Networks Gregor Bachmann Lorenzo Noci Thomas Hofmann BDL AAML 72 8 0 27 May 2022
Gaussian Pre-Activations in Neural Networks: Myth or Reality? Pierre Wolinski Julyan Arbel AI4CE 68 8 0 24 May 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 45 56 0 23 Feb 2022
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer Tycho F. A. van der Ouderaa Gunnar Rätsch Vincent Fortuin Mark van der Wilk BDL 18 44 0 22 Feb 2022
Transformers Can Do Bayesian Inference Samuel G. Müller Noah Hollmann Sebastian Pineda Arango Josif Grabocka Frank Hutter BDL UQCV 11 137 0 20 Dec 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 23 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
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 30 93 0 22 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 22 124 0 14 May 2021
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 13 60 0 17 May 2020
Why bigger is not always better: on finite and infinite neural networks Laurence Aitchison 173 51 0 17 Oct 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015