On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators

21 October 2016

Lawrence Carin

Papers citing "On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators"

30 / 30 papers shown

Title
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 75 0 0 25 Feb 2025
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics Daniel Paulin P. Whalley Neil K. Chada B. Leimkuhler BDL 46 4 0 14 Oct 2024
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics Haoyang Zheng Hengrong Du Qi Feng Wei Deng Guang Lin 39 4 0 13 May 2024
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 26 20 0 29 May 2023
An SDE for Modeling SAM: Theory and Insights Enea Monzio Compagnoni Luca Biggio Antonio Orvieto F. Proske Hans Kersting Aurélien Lucchi 23 13 0 19 Jan 2023
High-Frequency Space Diffusion Models for Accelerated MRI Chentao Cao Zhuoxu Cui Yue Wang Shaonan Liu Taijin Chen Hairong Zheng Dong Liang Yanjie Zhu DiffM MedIm 32 50 0 10 Aug 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 26 10 0 20 Feb 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao-quan Song Guang Lin FedML 27 16 0 09 Dec 2021
Uniform minorization condition and convergence bounds for discretizations of kinetic Langevin dynamics Alain Durmus Aurélien Enfroy Eric Moulines G. Stoltz 22 17 0 30 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 32 1,109 0 07 Jul 2021
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions Wei Deng Guang Lin F. Liang BDL 39 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 27 8 0 02 Oct 2020
Federated Stochastic Gradient Langevin Dynamics Khaoula El Mekkaoui Diego Mesquita P. Blomstedt Samuel Kaski FedML 19 24 0 23 Apr 2020
Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope Tolga Birdal Umut Simsekli 25 37 0 11 Apr 2019
Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning Huy N. Chau M. Rásonyi 19 10 0 25 Mar 2019
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 12 46 0 05 Sep 2018
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC Tolga Birdal Umut Simsekli M. Eken Slobodan Ilic 22 38 0 31 May 2018
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling Changyou Chen Ruiyi Zhang Wenlin Wang Bai Li Liqun Chen 18 86 0 29 May 2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem Andre Wibisono 15 177 0 22 Feb 2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods Difan Zou Pan Xu Quanquan Gu BDL 24 31 0 13 Feb 2018
On Connecting Stochastic Gradient MCMC and Differential Privacy Bai Li Changyou Chen Hao Liu Lawrence Carin 35 38 0 25 Dec 2017
Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen Chunyuan Li Liquan Chen Wenlin Wang Yunchen Pu Lawrence Carin TPM 34 57 0 04 Sep 2017
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization Pan Xu Jinghui Chen Difan Zou Quanquan Gu 31 200 0 20 Jul 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 25 101 0 16 Jun 2017
Fractional Langevin Monte Carlo: Exploring Lévy Driven Stochastic Differential Equations for Markov Chain Monte Carlo Umut Simsekli 33 45 0 12 Jun 2017
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks Nanyang Ye Zhanxing Zhu Rafał K. Mantiuk 11 20 0 13 Mar 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 50 41 0 23 Nov 2016
Quasi-stationary Monte Carlo and the ScaLE Algorithm M. Pollock Paul Fearnhead A. M. Johansen Gareth O. Roberts 25 18 0 12 Sep 2016
Stochastic Quasi-Newton Langevin Monte Carlo Umut Simsekli Roland Badeau A. Cemgil G. Richard BDL 14 60 0 10 Feb 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 22 319 0 23 Dec 2015