Bayesian Neural Network Priors Revisited

12 February 2021

Papers citing "Bayesian Neural Network Priors Revisited"

31 / 31 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 97 2 0 27 Nov 2024
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks Yoav Gelberg Tycho F. A. van der Ouderaa Mark van der Wilk Y. Gal AAML 37 4 0 10 Aug 2024
Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction Jiayang Shi Junyi Zhu D. Pelt K. Batenburg Matthew B. Blaschko 35 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 30 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 16 1 0 18 Mar 2023
Fixing Overconfidence in Dynamic Neural Networks Lassi Meronen Martin Trapp Andrea Pilzer Le Yang Arno Solin BDL 34 16 0 13 Feb 2023
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 18 52 0 11 Nov 2022
SPQR: An R Package for Semi-Parametric Density and Quantile Regression Steven G. Xu Reetam Majumder Brian J. Reich 16 0 0 26 Oct 2022
MARS: Meta-Learning as Score Matching in the Function Space Krunoslav Lehman Pavasovic Jonas Rothfuss Andreas Krause BDL 30 4 0 24 Oct 2022
Variational Model Perturbation for Source-Free Domain Adaptation Mengmeng Jing Xiantong Zhen Jingjing Li Cees G. M. Snoek 34 25 0 19 Oct 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 51 71 0 19 Jul 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 23 5 0 22 Jun 2022
Large-width asymptotics for ReLU neural networks with $α$ -Stable initializations Stefano Favaro S. Fortini Stefano Peluchetti 20 2 0 16 Jun 2022
How Tempering Fixes Data Augmentation in Bayesian Neural Networks Gregor Bachmann Lorenzo Noci Thomas Hofmann BDL AAML 80 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
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 40 10 0 17 May 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 52 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 31 44 0 22 Feb 2022
Transformers Can Do Bayesian Inference Samuel G. Müller Noah Hollmann Sebastian Pineda Arango Josif Grabocka Frank Hutter BDL UQCV 19 139 0 20 Dec 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 31 9 0 08 Oct 2021
Bayesian neural network unit priors and generalized Weibull-tail property M. Vladimirova Julyan Arbel Stéphane Girard BDL 54 9 0 06 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 34 11 0 06 Oct 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 46 93 0 22 Jun 2021
Precise characterization of the prior predictive distribution of deep ReLU networks Lorenzo Noci Gregor Bachmann Kevin Roth Sebastian Nowozin Thomas Hofmann BDL UQCV 16 32 0 11 Jun 2021
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect Lorenzo Noci Kevin Roth Gregor Bachmann Sebastian Nowozin Thomas Hofmann CML 30 23 0 11 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 21 37 0 10 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 29 124 0 14 May 2021
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 15 60 0 17 May 2020
Why bigger is not always better: on finite and infinite neural networks Laurence Aitchison 175 51 0 17 Oct 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015