Learning to Draw Samples with Amortized Stein Variational Gradient
Descent

Learning to Draw Samples with Amortized Stein Variational Gradient Descent

20 July 2017

Papers citing "Learning to Draw Samples with Amortized Stein Variational Gradient Descent"

19 / 19 papers shown

Title
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
S $^2$ AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic Safa Messaoud Billel Mokeddem Zhenghai Xue L. Pang Bo An Haipeng Chen Sanjay Chawla 41 3 0 02 May 2024
Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization Problems Dai Hai Nguyen Tetsuya Sakurai 29 1 0 31 Jul 2023
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks Forough Fazeli Asl M. Zhang Lizhen Lin 24 1 0 05 Mar 2023
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 27 19 0 25 Nov 2022
Towards Task-Prioritized Policy Composition Finn Rietz Erik Schaffernicht Todor Stoyanov J. A. Stork 22 0 0 20 Sep 2022
RSD-GAN: Regularized Sobolev Defense GAN Against Speech-to-Text Adversarial Attacks Mohammad Esmaeilpour Nourhene Chaalia P. Cardinal AAML 16 1 0 14 Jul 2022
Stein Variational Gradient Descent with Multiple Kernel Qingzhong Ai Shiyu Liu Lirong He Zenglin Xu 22 4 0 20 Jul 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 Gesine Reinert Yvik Swan 22 35 0 07 May 2021
A Non-Asymptotic Analysis for Stein Variational Gradient Descent Anna Korba Adil Salim Michael Arbel Giulia Luise A. Gretton 13 76 0 17 Jun 2020
Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration Anji Liu Yitao Liang Guy Van den Broeck OffRL 12 3 0 25 Feb 2020
Implicit Generative Modeling for Efficient Exploration Neale Ratzlaff Qinxun Bai Fuxin Li Wenyuan Xu 16 12 0 19 Nov 2019
AGAN: Towards Automated Design of Generative Adversarial Networks Hanchao Wang Jun Huan GAN AI4CE 6 37 0 25 Jun 2019
Stein Variational Gradient Descent as Moment Matching Qiang Liu Dilin Wang 17 37 0 27 Oct 2018
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 Unified Particle-Optimization Framework for Scalable Bayesian Sampling Changyou Chen Ruiyi Zhang Wenlin Wang Bai Li Liqun Chen 21 86 0 29 May 2018
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
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann A. Gretton BDL 107 324 0 09 Feb 2016