JaxSGMC: Modular stochastic gradient MCMC in JAX

16 May 2025

Papers citing "JaxSGMC: Modular stochastic gradient MCMC in JAX"

34 / 34 papers shown

Title
chemtrain: Learning Deep Potential Models via Automatic Differentiation and Statistical Physics Paul Fuchs Stephan Thaler Sebastien Röcken Julija Zavadlav DiffM 162 10 0 28 Aug 2024
Exploring Distributional Shifts in Large Language Models for Code Analysis Shushan Arakelyan Rocktim Jyoti Das Yi Mao Xiang Ren ALM 105 21 0 16 Mar 2023
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner Julija Zavadlav 95 21 0 15 Dec 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 97 39 0 25 Aug 2022
Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting Stephan Thaler Julija Zavadlav 74 71 0 02 Jun 2021
Exact Langevin Dynamics with Stochastic Gradients Adrià Garriga-Alonso Vincent Fortuin BDL 72 33 0 02 Feb 2021
Bayesian Graph Neural Networks for Molecular Property Prediction George Lamb Brooks Paige 75 12 0 25 Nov 2020
A Survey of Deep Active Learning Pengzhen Ren Yun Xiao Xiaojun Chang Po-Yao (Bernie) Huang Zhihui Li Brij B. Gupta Xiaojiang Chen Xin Wang 123 1,157 0 30 Aug 2020
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC Wei Deng Qi Feng Liyao (Mars) Gao F. Liang Guang Lin BDL 65 47 0 12 Aug 2020
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC Ruqi Zhang A. Feder Cooper Christopher De Sa 81 18 0 29 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 148 656 0 20 Feb 2020
Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro Du Phan Neeraj Pradhan M. Jankowiak 66 360 0 24 Dec 2019
Machine learning for molecular simulation Frank Noé A. Tkatchenko K. Müller C. Clementi AI4CE 80 665 0 07 Nov 2019
A Survey of Deep Learning Techniques for Autonomous Driving Sorin Grigorescu Bogdan Trasnea Tiberiu T. Cocias G. Macesanu 3DPC 114 1,411 0 17 Oct 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 81 138 0 16 Jul 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 88 278 0 11 Feb 2019
Stochastic Gradient MCMC with Repulsive Forces Víctor Gallego D. Insua BDL 60 37 0 30 Nov 2018
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 162 1,056 0 18 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,454 0 11 Oct 2018
TensorFlow Distributions Joshua V. Dillon I. Langmore Dustin Tran E. Brevdo Srinivas Vasudevan David A. Moore Brian Patton Alexander A. Alemi Matt Hoffman Rif A. Saurous GP 117 352 0 28 Nov 2017
sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 73 11 0 02 Oct 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 1.2K 20,944 0 17 Apr 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 859 5,853 0 05 Dec 2016
Distribution-Free Predictive Inference For Regression Jing Lei M. G'Sell Alessandro Rinaldo Robert Tibshirani Larry A. Wasserman 423 848 0 14 Apr 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 113 327 0 23 Dec 2015
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,819 0 10 Dec 2015
A Complete Recipe for Stochastic Gradient MCMC Yian Ma Tianqi Chen E. Fox BDL SyDa 104 490 0 15 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 935 9,372 0 06 Jun 2015
Consistency and fluctuations for stochastic gradient Langevin dynamics Yee Whye Teh Alexandre Hoang Thiery Sebastian J. Vollmer 122 235 0 01 Sep 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 133 914 0 17 Feb 2014
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 284 2,630 0 29 Jun 2012
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring S. Ahn Anoop Korattikara Balan Max Welling 79 306 0 27 Jun 2012
MCMC using Hamiltonian dynamics Radford M. Neal 315 3,284 0 09 Jun 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 199 4,321 0 18 Nov 2011