A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation

10 February 2016

Papers citing "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation"

46 / 296 papers shown

Title
Stochastic Gradient MCMC for State Space Models Christopher Aicher Yian Ma N. Foti E. Fox 33 21 0 22 Oct 2018
High-dimensional Varying Index Coefficient Models via Stein's Identity Sen Na Zhuoran Yang Zhaoran Wang Mladen Kolar 21 21 0 16 Oct 2018
A Riemann-Stein Kernel Method Alessandro Barp Christine J. Oates Emilio Porcu Mark Girolami 18 22 0 11 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
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Motonobu Kanagawa Philipp Hennig Dino Sejdinovic Bharath K. Sriperumbudur GP BDL 11 335 0 06 Jul 2018
Random Feature Stein Discrepancies Jonathan H. Huggins Lester W. Mackey 27 45 0 20 Jun 2018
Adaptive MCMC via Combining Local Samplers K. Shaloudegi András Gyorgy 24 1 0 11 Jun 2018
A Spectral Approach to Gradient Estimation for Implicit Distributions Jiaxin Shi Shengyang Sun Jun Zhu 14 90 0 07 Jun 2018
Stein Variational Gradient Descent Without Gradient J. Han Qiang Liu 6 45 0 07 Jun 2018
Sobolev Descent Youssef Mroueh Tom Sercu Anant Raj OT 21 1 0 30 May 2018
Bayesian posterior approximation via greedy particle optimization Futoshi Futami Zhenghang Cui Issei Sato Masashi Sugiyama 23 22 0 21 May 2018
Fisher Efficient Inference of Intractable Models Song Liu Takafumi Kanamori Wittawat Jitkrittum Yu Chen 29 14 0 18 May 2018
Weighted Poincaré inequalities, concentration inequalities and tail bounds related to the Stein kernels in dimension one Adrien Saumard 21 20 0 11 Apr 2018
Stein Points W. Chen Lester W. Mackey Jackson Gorham François‐Xavier Briol Chris J. Oates 13 101 0 27 Mar 2018
A particle-based variational approach to Bayesian Non-negative Matrix Factorization M. A. Masood Finale Doshi-Velez 12 11 0 16 Mar 2018
Exponentially Consistent Kernel Two-Sample Tests Shengyu Zhu Biao Chen Zhitang Chen 13 1 0 23 Feb 2018
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit Shengyu Zhu Biao Chen Pengfei Yang Zhitang Chen 20 3 0 21 Feb 2018
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification Yinhao Zhu N. Zabaras UQCV BDL 27 637 0 21 Jan 2018
Riemannian Stein Variational Gradient Descent for Bayesian Inference Chang-rui Liu Jun Zhu 11 67 0 30 Nov 2017
Stein Variational Message Passing for Continuous Graphical Models Dilin Wang Zhe Zeng Qiang Liu 32 3 0 20 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Sobolev GAN Youssef Mroueh Chun-Liang Li Tom Sercu Anant Raj Yu Cheng 8 117 0 14 Nov 2017
Message Passing Stein Variational Gradient Descent Jingwei Zhuo Chang-rui Liu Jiaxin Shi Jun Zhu Ning Chen Bo Zhang 30 90 0 13 Nov 2017
Action-depedent Control Variates for Policy Optimization via Stein's Identity Hao Liu Yihao Feng Yi Mao Dengyong Zhou Jian-wei Peng Qiang Liu 16 4 0 30 Oct 2017
On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests Krishnakumar Balasubramanian Tong Li M. Yuan 18 28 0 24 Sep 2017
Characteristic and Universal Tensor Product Kernels Z. Szabó Bharath K. Sriperumbudur 33 71 0 28 Aug 2017
Learning to Draw Samples with Amortized Stein Variational Gradient Descent Yihao Feng Dilin Wang Qiang Liu GAN BDL 21 79 0 20 Jul 2017
Learning Deep Energy Models: Contrastive Divergence vs. Amortized MLE Qiang Liu Dilin Wang 16 21 0 04 Jul 2017
Adversarial Feature Matching for Text Generation Yizhe Zhang Zhe Gan Kai Fan Zhi Chen Ricardo Henao Dinghan Shen Lawrence Carin GAN 13 333 0 12 Jun 2017
A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum Wenkai Xu Z. Szabó Kenji Fukumizu A. Gretton 27 102 0 22 May 2017
Gradient Estimators for Implicit Models Yingzhen Li Richard Turner 33 104 0 19 May 2017
Stein Variational Gradient Descent as Gradient Flow Qiang Liu OT 28 270 0 25 Apr 2017
Stein Variational Adaptive Importance Sampling J. Han Qiang Liu 8 28 0 18 Apr 2017
VAE Learning via Stein Variational Gradient Descent Yunchen Pu Zhe Gan Ricardo Henao Chunyuan Li Shaobo Han Lawrence Carin DRL 18 6 0 18 Apr 2017
The COM-negative binomial distribution: modeling overdispersion and ultrahigh zero-inflated count data Huiming Zhang Kai Tan Bo Li 11 12 0 15 Apr 2017
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 86 222 0 06 Mar 2017
Approximate Inference with Amortised MCMC Yingzhen Li Richard Turner Qiang Liu BDL 12 61 0 27 Feb 2017
Two Methods For Wild Variational Inference Qiang Liu Yihao Feng BDL 21 19 0 30 Nov 2016
Measuring Sample Quality with Diffusions Jackson Gorham Andrew B. Duncan Sandra Jeanne Vollmer Lester W. Mackey 30 116 0 21 Nov 2016
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning Dilin Wang Qiang Liu GAN BDL 38 118 0 06 Nov 2016
Black-box Importance Sampling Qiang Liu J. Lee FAtt 17 73 0 17 Oct 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 19 1,067 0 16 Aug 2016
Uncertain programming model for multi-item solid transportation problem Hasan Dalman 16 722 0 31 May 2016
Convergence Rates for a Class of Estimators Based on Stein's Method Chris J. Oates Jon Cockayne F. Briol Mark Girolami 19 57 0 10 Mar 2016
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann A. Gretton BDL 107 324 0 09 Feb 2016
Measuring Sample Quality with Stein's Method Jackson Gorham Lester W. Mackey 33 223 0 09 Jun 2015