Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks

10 February 2025

Papers citing "Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks"

17 / 17 papers shown

Title
Paths and Ambient Spaces in Neural Loss Landscapes Daniel Dold Julius Kobialka Nicolai Palm Emanuel Sommer David Rügamer Oliver Durr AI4CE 101 0 0 05 Mar 2025
Stochastic Localization via Iterative Posterior Sampling Louis Grenioux Maxence Noble Marylou Gabrié Alain Durmus DiffM 62 16 0 16 Feb 2024
Focusing on Difficult Directions for Learning HMC Trajectory Lengths Pavel Sountsov Matt Hoffman 61 10 0 22 Oct 2021
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension Alain Durmus A. Eberle 60 20 0 02 Aug 2021
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 67 385 0 29 Apr 2021
Bayesian Neural Network Priors Revisited Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard Turner Mark van der Wilk Laurence Aitchison BDL UQCV 99 140 0 12 Feb 2021
A Bayesian neural network predicts the dissolution of compact planetary systems M. Cranmer Daniel Tamayo H. Rein Peter W. Battaglia S. Hadden P. Armitage S. Ho D. Spergel BDL 81 27 0 11 Jan 2021
Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting Adam D. Cobb Brian Jalaian BDL 63 76 0 14 Oct 2020
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 62 144 0 17 Jul 2019
$Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC$ Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC Aki Vehtari Andrew Gelman Daniel P. Simpson Bob Carpenter Paul-Christian Bürkner 37 930 0 19 Mar 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 74 276 0 11 Feb 2019
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 193 632 0 01 Jul 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 268 8,876 0 25 Aug 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 670 131,414 0 12 Jun 2017
MCMC using Hamiltonian dynamics Radford M. Neal 290 3,280 0 09 Jun 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 162 4,297 0 18 Nov 2011
Elliptical slice sampling Iain Murray Ryan P. Adams D. MacKay 124 465 0 31 Dec 2009