A Unified Particle-Optimization Framework for Scalable Bayesian Sampling

A Unified Particle-Optimization Framework for Scalable Bayesian Sampling

29 May 2018

Papers citing "A Unified Particle-Optimization Framework for Scalable Bayesian Sampling"

17 / 17 papers shown

Title
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 50 0 0 08 May 2025
Gradient-based Sample Selection for Faster Bayesian Optimization Qiyu Wei Haowei Wang Zirui Cao Songhao Wang Richard Allmendinger Mauricio A Álvarez 24 0 0 10 Apr 2025
ELBOing Stein: Variational Bayes with Stein Mixture Inference Ola Rønning Eric T. Nalisnick Christophe Ley Padhraic Smyth Thomas Hamelryck BDL 52 1 0 30 Oct 2024
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework Fangyikang Wang Huminhao Zhu Chao Zhang Han Zhao Hui Qian 24 5 0 27 Dec 2023
Discrete Langevin Sampler via Wasserstein Gradient Flow Haoran Sun H. Dai Bo Dai Haomin Zhou Dale Schuurmans BDL 42 19 0 29 Jun 2022
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel Yindong Chen Yiwei Wang Lulu Kang Chun Liu 18 1 0 21 Nov 2021
Relative Entropy Gradient Sampler for Unnormalized Distributions Xingdong Feng Yuan Gao Jian Huang Yuling Jiao Xu Liu 33 7 0 06 Oct 2021
Stein Variational Gradient Descent with Multiple Kernel Qingzhong Ai Shiyu Liu Lirong He Zenglin Xu 17 4 0 20 Jul 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 46 93 0 22 Jun 2021
Stein's Method Meets Computational Statistics: A Review of Some Recent Developments Andreas Anastasiou Alessandro Barp F. Briol B. Ebner Robert E. Gaunt ... Qiang Liu Lester W. Mackey Chris J. Oates G. Reinert Yvik Swan 22 35 0 07 May 2021
Stein Variational Gradient Descent: many-particle and long-time asymptotics Nikolas Nusken D. M. Renger 24 22 0 25 Feb 2021
Straight-Through Estimator as Projected Wasserstein Gradient Flow Pengyu Cheng YooJung Choi Yitao Liang Dinghan Shen Ricardo Henao Guy Van den Broeck 22 14 0 05 Oct 2019
Stein Point Markov Chain Monte Carlo W. Chen Alessandro Barp François‐Xavier Briol Jackson Gorham Mark Girolami Lester W. Mackey Chris J. Oates 30 56 0 09 May 2019
Accelerated Flow for Probability Distributions Amirhossein Taghvaei P. Mehta 26 30 0 10 Jan 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
Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang Changyou Chen Chunyuan Li Lawrence Carin 14 66 0 09 Aug 2018
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 32 158 0 21 Oct 2016