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Consistency and fluctuations for stochastic gradient Langevin dynamics

1 September 2014

Yee Whye Teh

Alexandre Hoang Thiery

Sebastian J. Vollmer

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

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Continuous Policy and Value Iteration for Stochastic Control Problems and Its Convergence Qi Feng Gu Wang 19 0 0 09 Jun 2025
Accelerating Constrained Sampling: A Large Deviations Approach Yingli Wang Changwei Tu Xiaoyu Wang Lingjiong Zhu 27 0 0 09 Jun 2025
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JaxSGMC: Modular stochastic gradient MCMC in JAX Stephan Thaler Paul Fuchs Ana Cukarska Julija Zavadlav BDL 221 2 0 16 May 2025
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo Hyunsu Kim G. Nam Chulhee Yun Hongseok Yang Juho Lee BDL UQCV 105 0 0 02 Mar 2025
Self-normalized Cramér-type Moderate Deviation of Stochastic Gradient Langevin Dynamics Hongsheng Dai Xiequan Fan Jianya Lu 42 1 0 29 Oct 2024
Drift to Remember Jin Du Xinsong Zhang Hao Shen Xun Xian Ganghua Wang Jiawei Zhang Yuhong Yang Na Li Jia Liu Jie Ding CLL 53 0 0 21 Sep 2024
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling Jian Xu Shian Du Junmei Yang Qianli Ma Delu Zeng BDL 62 0 0 13 Aug 2024
Generative vs. Discriminative modeling under the lens of uncertainty quantification Elouan Argouarc'h François Desbouvries Eric Barat Eiji Kawasaki UQCV 78 0 0 13 Jun 2024
Taming Score-Based Diffusion Priors for Infinite-Dimensional Nonlinear Inverse Problems Lorenzo Baldassari Ali Siahkoohi Josselin Garnier K. Sølna Maarten V. de Hoop DiffM 129 2 0 24 May 2024
Robust Approximate Sampling via Stochastic Gradient Barker Dynamics Lorenzo Mauri Giacomo Zanella 88 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 110 9 0 14 May 2024
Stochastic Gradient MCMC for Massive Geostatistical Data M. Abba Brian J. Reich Reetam Majumder Brandon Feng 57 1 0 07 May 2024
Causal-StoNet: Causal Inference for High-Dimensional Complex Data Yaxin Fang Faming Liang CML 73 2 0 27 Mar 2024
An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling Xunpeng Huang Hanze Dong Difan Zou Tong Zhang 82 0 0 10 Mar 2024
Scalable Bayesian inference for the generalized linear mixed model S. Berchuck Felipe A. Medeiros Sayan Mukherjee Andrea Agazzi 72 0 0 05 Mar 2024
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo Haoyang Zheng Wei Deng Christian Moya Guang Lin 103 6 0 22 Jan 2024
Sampling and estimation on manifolds using the Langevin diffusion Karthik Bharath Alexander Lewis Akash Sharma M. Tretyakov DiffM 156 5 0 22 Dec 2023
Asynchronous Local Computations in Distributed Bayesian Learning Kinjal Bhar He Bai Jemin George Carl E. Busart 46 0 0 06 Nov 2023
Langevin Quasi-Monte Carlo Sifan Liu BDL 57 4 0 22 Sep 2023
Constructing Semantics-Aware Adversarial Examples with Probabilistic Perspective Andi Zhang Mingtian Zhang Damon J. Wischik GAN AAML 62 1 0 01 Jun 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 114 23 0 29 May 2023
Bayes Complexity of Learners vs Overfitting Grzegorz Gluch R. Urbanke UQCV BDL 20 1 0 13 Mar 2023
Piecewise Deterministic Markov Processes for Bayesian Neural Networks Ethan Goan Dimitri Perrin Kerrie Mengersen Clinton Fookes 69 0 0 17 Feb 2023
Fast Replica Exchange Stochastic Gradient Langevin Dynamics Guanxun Li Guang Lin Zecheng Zhang Quan Zhou 444 4 0 05 Jan 2023
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models Xinyu Zhang Cheng Li 71 0 0 18 Dec 2022
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner Julija Zavadlav 109 21 0 15 Dec 2022
Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants Liyao (Mars) Gao J. Nathan Kutz AI4CE 90 22 0 19 Nov 2022
Preferential Subsampling for Stochastic Gradient Langevin Dynamics Srshti Putcha Christopher Nemeth Paul Fearnhead 61 0 0 28 Oct 2022
A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Ya-Ping Hsieh Andreas Krause 87 4 0 25 Oct 2022
Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network Siqi Liang Y. Sun F. Liang BDL 71 11 0 09 Oct 2022
Functional Central Limit Theorem and Strong Law of Large Numbers for Stochastic Gradient Langevin Dynamics A. Lovas Miklós Rásonyi 34 1 0 05 Oct 2022
Tuning Stochastic Gradient Algorithms for Statistical Inference via Large-Sample Asymptotics Jeffrey Negrea Jun Yang Haoyue Feng Daniel M. Roy Jonathan H. Huggins 65 1 0 25 Jul 2022
A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics Lei Li Yuliang Wang 106 11 0 19 Jul 2022
Bayesian Learning of Parameterised Quantum Circuits Samuel Duffield Marcello Benedetti Matthias Rosenkranz 60 11 0 15 Jun 2022
Concentration analysis of multivariate elliptic diffusion processes Cathrine Aeckerle-Willems Claudia Strauch Lukas Trottner 103 1 0 07 Jun 2022
Distributed data analytics Richard Mortier Hamed Haddadi S. S. Rodríguez Liang Wang 74 2 0 26 Mar 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 81 10 0 20 Feb 2022
Energy-Based Models for Functional Data using Path Measure Tilting Jen Ning Lim Sebastian J. Vollmer Lorenz Wolf Andrew Duncan 80 3 0 04 Feb 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao Song Guang Lin FedML 93 17 0 09 Dec 2021
Time-independent Generalization Bounds for SGLD in Non-convex Settings Tyler Farghly Patrick Rebeschini 99 24 0 25 Nov 2021
Deep Bayesian inference for seismic imaging with tasks Ali Siahkoohi G. Rizzuti Felix J. Herrmann BDL UQCV 99 21 0 10 Oct 2021
Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics Benjamin J. Zhang Youssef M. Marzouk K. Spiliopoulos 48 8 0 18 Aug 2021
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise Guodong Zhang Kyle Hsu Jianing Li Chelsea Finn Roger C. Grosse 92 40 0 21 Jul 2021
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo Vyacheslav Kungurtsev Adam D. Cobb T. Javidi Brian Jalaian 90 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 242 1,178 0 07 Jul 2021
Stein ICP for Uncertainty Estimation in Point Cloud Matching F. A. Maken Fabio Ramos Lionel Ott 3DV 3DPC 65 27 0 07 Jun 2021
Quantifying the mini-batching error in Bayesian inference for Adaptive Langevin dynamics Inass Sekkat G. Stoltz 78 4 0 21 May 2021