Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling

15 June 2022

Papers citing "Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling"

7 / 7 papers shown

Title
The Architecture and Evaluation of Bayesian Neural Networks Alisa Sheinkman Sara Wade UQCV BDL 67 0 0 14 Mar 2025
Function-Space MCMC for Bayesian Wide Neural Networks Lucia Pezzetti Stefano Favaro Stefano Peluchetti BDL 94 0 0 26 Aug 2024
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models Gianni Franchi Olivier Laurent Maxence Leguéry Andrei Bursuc Andrea Pilzer Angela Yao UQCV BDL 15 4 0 23 Dec 2023
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks Chanwoo Chun Daniel D. Lee BDL 25 2 0 17 May 2023
Bayesian Interpolation with Deep Linear Networks Boris Hanin Alexander Zlokapa 34 25 0 29 Dec 2022
Why bigger is not always better: on finite and infinite neural networks Laurence Aitchison 173 51 0 17 Oct 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 266 0 13 Jun 2018