Understanding and Accelerating Particle-Based Variational Inference

4 July 2018

Jun Zhu

Lawrence Carin

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Papers citing "Understanding and Accelerating Particle-Based Variational Inference"

24 / 24 papers shown

Title
Scalable Thompson Sampling via Optimal Transport Ruiyi Zhang Zheng Wen Changyou Chen Lawrence Carin OT 55 20 0 19 Feb 2019
Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang Changyou Chen Chunyuan Li Lawrence Carin 52 68 0 09 Aug 2018
A Stein variational Newton method Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl 90 117 0 08 Jun 2018
A Spectral Approach to Gradient Estimation for Implicit Distributions Jiaxin Shi Shengyang Sun Jun Zhu 54 91 0 07 Jun 2018
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling Changyou Chen Ruiyi Zhang Wenlin Wang Bai Li Liqun Chen 47 89 0 29 May 2018
Bayesian posterior approximation via greedy particle optimization Futoshi Futami Zhenghang Cui Issei Sato Masashi Sugiyama 62 22 0 21 May 2018
Stein Points W. Chen Lester W. Mackey Jackson Gorham François‐Xavier Briol Chris J. Oates 58 102 0 27 Mar 2018
A Fast Proximal Point Method for Computing Exact Wasserstein Distance Yujia Xie Xiangfeng Wang Ruijia Wang H. Zha 42 18 0 12 Feb 2018
Riemannian Stein Variational Gradient Descent for Bayesian Inference Chang-rui Liu Jun Zhu 55 67 0 30 Nov 2017
Particle Optimization in Stochastic Gradient MCMC Changyou Chen Ruiyi Zhang 34 10 0 29 Nov 2017
Message Passing Stein Variational Gradient Descent Jingwei Zhuo Chang-rui Liu Jiaxin Shi Jun Zhu Ning Chen Bo Zhang 54 92 0 13 Nov 2017
Gradient Estimators for Implicit Models Yingzhen Li Richard Turner 97 108 0 19 May 2017
Stein Variational Gradient Descent as Gradient Flow Qiang Liu OT 66 275 0 25 Apr 2017
Stein Variational Policy Gradient Yang Liu Prajit Ramachandran Qiang Liu Jian-wei Peng 60 139 0 07 Apr 2017
Reinforcement Learning with Deep Energy-Based Policies Tuomas Haarnoja Haoran Tang Pieter Abbeel Sergey Levine 83 1,339 0 27 Feb 2017
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning Dilin Wang Qiang Liu GAN BDL 112 120 0 06 Nov 2016
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 66 161 0 21 Oct 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 63 1,091 0 16 Aug 2016
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds Hongyi Zhang Sashank J. Reddi S. Sra 85 240 0 23 May 2016
A Variational Perspective on Accelerated Methods in Optimization Andre Wibisono Ashia Wilson Michael I. Jordan 85 572 0 14 Mar 2016
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 286 4,167 0 21 May 2015
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 180 4,251 0 04 Jun 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 232 2,619 0 29 Jun 2012
MCMC using Hamiltonian dynamics Radford M. Neal 288 3,276 0 09 Jun 2012