Consistency and fluctuations for stochastic gradient Langevin dynamics

1 September 2014

Papers citing "Consistency and fluctuations for stochastic gradient Langevin dynamics"

50 / 56 papers shown

Title
JaxSGMC: Modular stochastic gradient MCMC in JAX Stephan Thaler Paul Fuchs Ana Cukarska Julija Zavadlav BDL 43 2 0 16 May 2025
Drift to Remember Jin Du Xinsong Zhang Hao Shen Xun Xian Ganghua Wang Jiawei Zhang Yuhong Yang Na Li Jia Liu Jie Ding CLL 21 0 0 21 Sep 2024
Robust Approximate Sampling via Stochastic Gradient Barker Dynamics Lorenzo Mauri Giacomo Zanella 32 3 0 14 May 2024
Energy-based Hopfield Boosting for Out-of-Distribution Detection Claus Hofmann Simon Schmid Bernhard Lehner Daniel Klotz Sepp Hochreiter OODD 45 8 0 14 May 2024
Scalable Bayesian inference for the generalized linear mixed model S. Berchuck Felipe A. Medeiros Sayan Mukherjee Andrea Agazzi 32 0 0 05 Mar 2024
Sampling and estimation on manifolds using the Langevin diffusion Karthik Bharath Alexander Lewis Akash Sharma M. Tretyakov DiffM 77 5 0 22 Dec 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 28 20 0 29 May 2023
Fast Replica Exchange Stochastic Gradient Langevin Dynamics Guanxun Li Guang Lin Zecheng Zhang Quan Zhou 179 4 0 05 Jan 2023
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models Xinyu Zhang Cheng Li 28 0 0 18 Dec 2022
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner Julija Zavadlav 35 21 0 15 Dec 2022
A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Ya-Ping Hsieh Andreas Krause 40 4 0 25 Oct 2022
A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics Lei Li Yuliang Wang 39 11 0 19 Jul 2022
Bayesian Learning of Parameterised Quantum Circuits Samuel Duffield Marcello Benedetti Matthias Rosenkranz 19 11 0 15 Jun 2022
Distributed data analytics Richard Mortier Hamed Haddadi S. S. Rodríguez Liang Wang 29 2 0 26 Mar 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 41 10 0 20 Feb 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi Ma Zhao Song Guang Lin FedML 30 16 0 09 Dec 2021
Deep Bayesian inference for seismic imaging with tasks Ali Siahkoohi G. Rizzuti Felix J. Herrmann BDL UQCV 40 21 0 10 Oct 2021
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo Vyacheslav Kungurtsev Adam D. Cobb T. Javidi Brian Jalaian 51 4 0 15 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 59 1,111 0 07 Jul 2021
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions Wei Deng Guang Lin F. Liang BDL 42 27 0 19 Oct 2020
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction Wei Deng Qi Feng G. Karagiannis Guang Lin F. Liang 33 8 0 02 Oct 2020
Shape Matters: Understanding the Implicit Bias of the Noise Covariance Jeff Z. HaoChen Colin Wei J. Lee Tengyu Ma 29 93 0 15 Jun 2020
Powering One-shot Topological NAS with Stabilized Share-parameter Proxy Ronghao Guo Chen Lin Chuming Li Keyu Tian Ming Sun Lu Sheng Junjie Yan BDL 29 17 0 21 May 2020
Federated Stochastic Gradient Langevin Dynamics Khaoula El Mekkaoui Diego Mesquita P. Blomstedt Samuel Kaski FedML 21 24 0 23 Apr 2020
Estimating Motion Uncertainty with Bayesian ICP F. A. Maken F. Ramos Lionel Ott 3DPC 30 9 0 16 Apr 2020
Predicting the outputs of finite deep neural networks trained with noisy gradients Gadi Naveh Oded Ben-David H. Sompolinsky Zohar Ringel 19 20 0 02 Apr 2020
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng Xiao Zhang F. Liang Guang Lin BDL 34 42 0 23 Oct 2019
Aggregated Gradient Langevin Dynamics Chao Zhang Jiahao Xie Zebang Shen P. Zhao Tengfei Zhou Hui Qian 31 1 0 21 Oct 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 22 134 0 16 Jul 2019
On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case M. Barkhagen N. H. Chau '. Moulines Miklós Rásonyi S. Sabanis Ying Zhang 21 37 0 06 Dec 2018
Finding Mixed Nash Equilibria of Generative Adversarial Networks Ya-Ping Hsieh Chen Liu S. Chakrabartty GAN 24 91 0 23 Oct 2018
Fluctuation-dissipation relations for stochastic gradient descent Sho Yaida 32 73 0 28 Sep 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 12 46 0 05 Sep 2018
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling Changyou Chen Ruiyi Zhang Wenlin Wang Bai Li Liqun Chen 21 86 0 29 May 2018
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors Gintare Karolina Dziugaite Daniel M. Roy MLT 30 144 0 26 Dec 2017
On Connecting Stochastic Gradient MCMC and Differential Privacy Bai Li Changyou Chen Hao Liu Lawrence Carin 41 38 0 25 Dec 2017
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference Jonathan H. Huggins Ryan P. Adams Tamara Broderick 24 32 0 26 Sep 2017
Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen Chunyuan Li Liquan Chen Wenlin Wang Yunchen Pu Lawrence Carin TPM 46 57 0 04 Sep 2017
Hamiltonian Monte Carlo with Energy Conserving Subsampling Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran M. Villani 29 62 0 02 Aug 2017
Mini-batch Tempered MCMC Dangna Li W. Wong 26 5 0 31 Jul 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 30 101 0 16 Jun 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling Zhe Gan Chunyuan Li Changyou Chen Yunchen Pu Qinliang Su Lawrence Carin BDL UQCV 53 41 0 23 Nov 2016
Measuring Sample Quality with Diffusions Jackson Gorham Andrew B. Duncan Sandra Jeanne Vollmer Lester W. Mackey 38 116 0 21 Nov 2016
Multilevel Monte Carlo for Scalable Bayesian Computations M. Giles Tigran Nagapetyan Lukasz Szpruch Sebastian J. Vollmer K. Zygalakis 21 9 0 15 Sep 2016
Quasi-stationary Monte Carlo and the ScaLE Algorithm M. Pollock Paul Fearnhead A. M. Johansen Gareth O. Roberts 33 18 0 12 Sep 2016
Merging MCMC Subposteriors through Gaussian-Process Approximations Christopher Nemeth Chris Sherlock 22 49 0 27 May 2016
Coresets for Scalable Bayesian Logistic Regression Jonathan H. Huggins Trevor Campbell Tamara Broderick 24 217 0 20 May 2016
Quantifying the accuracy of approximate diffusions and Markov chains Jonathan H. Huggins James Zou 49 29 0 20 May 2016
Stochastic Quasi-Newton Langevin Monte Carlo Umut Simsekli Roland Badeau A. Cemgil G. Richard BDL 14 61 0 10 Feb 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 27 320 0 23 Dec 2015