Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning

6 November 2016

Papers citing "Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning"

50 / 73 papers shown

Title
Denoising Fisher Training For Neural Implicit Samplers Weijian Luo Wei Deng 30 0 0 03 Nov 2024
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow Chen-Hao Chao Chien Feng Wei-Fang Sun Cheng-Kuang Lee Simon See Chun-Yi Lee 38 1 0 22 May 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
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
Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows Mingxuan Yi Song Liu DRL 20 8 0 31 Oct 2023
Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization Problems Dai Hai Nguyen Tetsuya Sakurai 24 1 0 31 Jul 2023
Entropy-based Training Methods for Scalable Neural Implicit Sampler Weijian Luo Boya Zhang Zhihua Zhang 26 10 0 08 Jun 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 27 7 0 27 May 2023
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes Ba-Hien Tran B. Shahbaba Stephan Mandt Maurizio Filippone SyDa BDL UQCV 12 5 0 09 Feb 2023
MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows Mingxuan Yi Zhanxing Zhu Song Liu GAN 24 13 0 02 Feb 2023
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates Louis Sharrock Christopher Nemeth BDL 17 8 0 26 Jan 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
Spherical Sliced-Wasserstein Clément Bonet P. Berg Nicolas Courty Françcois Septier Lucas Drumetz Minh Pham 27 27 0 17 Jun 2022
Equivariant Descriptor Fields: SE(3)-Equivariant Energy-Based Models for End-to-End Visual Robotic Manipulation Learning Hyunwoo Ryu Jeong-Hoon Lee Honglak Lee Jongeun Choi 37 53 0 16 Jun 2022
Emergence of Theory of Mind Collaboration in Multiagent Systems Luyao Yuan Zipeng Fu Linqi Zhou Kexin Yang Song-Chun Zhu 46 10 0 30 Sep 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
Generative Particle Variational Inference via Estimation of Functional Gradients Neale Ratzlaff Qinxun Bai Fuxin Li W. Xu BDL DRL 18 0 0 01 Mar 2021
Kernel Stein Generative Modeling Wei-Cheng Chang Chun-Liang Li Youssef Mroueh Yiming Yang DiffM BDL 33 5 0 06 Jul 2020
Stochastic Stein Discrepancies Jackson Gorham Anant Raj Lester W. Mackey 14 37 0 06 Jul 2020
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
Stabilizing Training of Generative Adversarial Nets via Langevin Stein Variational Gradient Descent Dong Wang Xiaoqian Qin F. Song Li Cheng GAN 6 22 0 22 Apr 2020
Score-Guided Generative Adversarial Networks Minhyeok Lee Junhee Seok EGVM 16 15 0 09 Apr 2020
Scalable Approximate Inference and Some Applications Jun Han BDL 20 1 0 07 Mar 2020
Training Deep Energy-Based Models with f-Divergence Minimization Lantao Yu Yang Song Jiaming Song Stefano Ermon 176 42 0 06 Mar 2020
GenDICE: Generalized Offline Estimation of Stationary Values Ruiyi Zhang Bo Dai Lihong Li Dale Schuurmans OffRL 6 172 0 21 Feb 2020
The reproducing Stein kernel approach for post-hoc corrected sampling Liam Hodgkinson R. Salomone Fred Roosta 32 27 0 25 Jan 2020
A Near-Optimal Gradient Flow for Learning Neural Energy-Based Models Yang Wu Pengxu Wei Liang Lin 14 0 0 31 Oct 2019
Adversarial Fisher Vectors for Unsupervised Representation Learning Shuangfei Zhai Walter A. Talbott Carlos Guestrin J. Susskind GAN 19 8 0 29 Oct 2019
Stein Variational Gradient Descent With Matrix-Valued Kernels Dilin Wang Ziyang Tang Chandrajit L. Bajaj Qiang Liu 25 62 0 28 Oct 2019
Towards Robust, Locally Linear Deep Networks Guang-He Lee David Alvarez-Melis Tommi Jaakkola ODL 11 48 0 07 Jul 2019
Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning Jianwen Xie Zilong Zheng Xiaolin Fang Song-Chun Zhu Ying Nian Wu 18 4 0 07 Feb 2019
Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning Ying Wen Yaodong Yang Rui Luo Jun Wang Wei Pan LRM 16 146 0 26 Jan 2019
Deep Generative Learning via Variational Gradient Flow Yuan Gao Yuling Jiao Yang Wang Yao Wang Can Yang Shunkang Zhang 19 36 0 24 Jan 2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution Chunyuan Li Ke Bai Jianqiao Li Guoyin Wang Changyou Chen Lawrence Carin 11 10 0 03 Jan 2019
FRAME Revisited: An Interpretation View Based on Particle Evolution Xu Cai Yang Wu Guanbin Li Ziliang Chen Liang Lin 13 2 0 04 Dec 2018
Stein Variational Gradient Descent as Moment Matching Qiang Liu Dilin Wang 12 37 0 27 Oct 2018
Stein Neural Sampler Tianyang Hu Zixiang Chen Hanxi Sun Jincheng Bai Mao Ye Guang Cheng SyDa GAN 17 34 0 08 Oct 2018
Parametric generation of conditional geological realizations using generative neural networks Shing Chan A. Elsheikh OOD GAN AI4CE 21 101 0 13 Jul 2018
Understanding and Accelerating Particle-Based Variational Inference Chang-rui Liu Jingwei Zhuo Pengyu Cheng Ruiyi Zhang Jun Zhu Lawrence Carin 9 14 0 04 Jul 2018
Deep Generative Models with Learnable Knowledge Constraints Zhiting Hu Zichao Yang Ruslan Salakhutdinov Xiaodan Liang Lianhui Qin Haoye Dong Eric P. Xing BDL AI4CE 17 77 0 26 Jun 2018
Random Feature Stein Discrepancies Jonathan H. Huggins Lester W. Mackey 24 45 0 20 Jun 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 22 68 0 06 Jun 2018
Whitening and Coloring batch transform for GANs Aliaksandr Siarohin E. Sangineto N. Sebe 19 49 0 01 Jun 2018
Distribution Aware Active Learning Arash Mehrjou Mehran Khodabandeh Greg Mori 28 4 0 23 May 2018
Fisher Efficient Inference of Intractable Models Song Liu Takafumi Kanamori Wittawat Jitkrittum Yu Chen 21 14 0 18 May 2018
Composable Deep Reinforcement Learning for Robotic Manipulation Tuomas Haarnoja Vitchyr H. Pong Aurick Zhou Murtaza Dalal Pieter Abbeel Sergey Levine 19 230 0 19 Mar 2018
Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect Xiang Wei Boqing Gong Zixia Liu W. Lu Liqiang Wang GAN 6 260 0 05 Mar 2018
Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models Atsushi Nitanda Taiji Suzuki GAN 18 12 0 07 Jan 2018
Stochastic Maximum Likelihood Optimization via Hypernetworks Abdul-Saboor Sheikh Kashif Rasul A. Merentitis Urs M. Bergmann 50 18 0 04 Dec 2017