Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting

14 October 2020

Papers citing "Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting"

29 / 29 papers shown

Title
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 81 0 0 03 Jan 2025
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics Daniel Paulin Peter Whalley Neil K. Chada Benedict Leimkuhler BDL 67 4 0 14 Oct 2024
Gradient-free variational learning with conditional mixture networks Conor Heins Hao Wu Dimitrije Marković Alexander Tschantz Jeff Beck Christopher L. Buckley BDL 59 2 0 29 Aug 2024
CONFINE: Conformal Prediction for Interpretable Neural Networks Linhui Huang S. Lala N. Jha 154 2 0 01 Jun 2024
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks Meet P. Vadera Adam D. Cobb B. Jalaeian Benjamin M. Marlin BDL UQCV 47 16 0 08 Jul 2020
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? Angelos Filos P. Tigas R. McAllister Nicholas Rhinehart Sergey Levine Y. Gal 35 185 0 26 Jun 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 54 314 0 15 Feb 2020
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat Brian Karrer Daniel R. Jiang Sam Daulton Benjamin Letham A. Wilson E. Bakshy 41 93 0 14 Oct 2019
Bayesian Inference for Large Scale Image Classification Jonathan Heek Nal Kalchbrenner UQCV BDL 91 33 0 09 Aug 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 56 144 0 17 Jul 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 53 298 0 04 Jun 2019
Ensemble Distribution Distillation A. Malinin Bruno Mlodozeniec Mark Gales UQCV 54 232 0 30 Apr 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 48 105 0 09 Mar 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 54 275 0 11 Feb 2019
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 90 1,043 0 18 Oct 2018
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration Jacob R. Gardner Geoff Pleiss D. Bindel Kilian Q. Weinberger A. Wilson GP 61 1,088 0 28 Sep 2018
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning Stefan Depeweg José Miguel Hernández-Lobato Finale Doshi-Velez Steffen Udluft UQCV PER BDL UD 46 27 0 19 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 127 8,807 0 25 Aug 2017
Self-Normalizing Neural Networks Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter 209 2,496 0 08 Jun 2017
Deep Bayesian Active Learning with Image Data Y. Gal Riashat Islam Zoubin Ghahramani BDL UQCV 46 1,717 0 08 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 463 5,748 0 05 Dec 2016
An introduction to sampling via measure transport Youssef Marzouk Tarek A. El-Moselhy M. Parno Alessio Spantini OT 59 89 0 16 Feb 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 439 9,233 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 102 1,878 0 20 May 2015
Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models Yichuan Zhang Charles Sutton 50 20 0 15 Jun 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 62 902 0 17 Feb 2014
Bayesian Active Learning for Classification and Preference Learning N. Houlsby Ferenc Huszár Zoubin Ghahramani M. Lengyel 58 901 0 24 Dec 2011
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 128 4,275 0 18 Nov 2011
Split Hamiltonian Monte Carlo Babak Shahbaba Shiwei Lan W. Johnson Radford M. Neal 127 92 0 29 Jun 2011