Message Passing Stein Variational Gradient Descent

13 November 2017

Jun Zhu

Papers citing "Message Passing Stein Variational Gradient Descent"

22 / 22 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
Flow Matching Ergodic Coverage Max Muchen Sun Allison Pinosky Todd Murphey 30 0 0 24 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
Accelerating Convergence of Stein Variational Gradient Descent via Deep Unfolding Yuya Kawamura Satoshi Takabe BDL 26 0 0 23 Feb 2024
Stein Variational Belief Propagation for Multi-Robot Coordination Jana Pavlasek J. Mah Ruihan Xu Odest Chadwicke Jenkins Fabio Ramos 13 2 0 28 Nov 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 27 7 0 27 May 2023
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 22 19 0 25 Nov 2022
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent Jiaxin Shi Lester W. Mackey 23 18 0 17 Nov 2022
Grassmann Stein Variational Gradient Descent Xingtu Liu Harrison Zhu Jean-François Ton George Wynne Andrew Duncan 23 12 0 07 Feb 2022
Low-rank variational Bayes correction to the Laplace method J. van Niekerk Haavard Rue BDL 13 13 0 25 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
Sampling with Mirrored Stein Operators Jiaxin Shi Chang-rui Liu Lester W. Mackey 45 19 0 23 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
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent Rahif Kassab Osvaldo Simeone FedML 20 45 0 11 Sep 2020
Blindness of score-based methods to isolated components and mixing proportions Wenliang K. Li Heishiro Kanagawa 15 34 0 23 Aug 2020
Stein Variational Gradient Descent With Matrix-Valued Kernels Dilin Wang Ziyang Tang Chandrajit L. Bajaj Qiang Liu 25 62 0 28 Oct 2019
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability Shaowu Pan Karthik Duraisamy 23 136 0 09 Jun 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
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 Stein variational Newton method Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl 61 114 0 08 Jun 2018
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 86 222 0 06 Mar 2017
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann A. Gretton BDL 107 324 0 09 Feb 2016