Title
Stein Points W. Chen Lester W. Mackey Jackson Gorham François‐Xavier Briol Chris J. Oates 56 102 0 27 Mar 2018
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification Yinhao Zhu N. Zabaras UQCV BDL 56 640 0 21 Jan 2018
Riemannian Stein Variational Gradient Descent for Bayesian Inference Chang-rui Liu Jun Zhu 49 67 0 30 Nov 2017
Message Passing Stein Variational Gradient Descent Jingwei Zhuo Chang-rui Liu Jiaxin Shi Jun Zhu Ning Chen Bo Zhang 47 91 0 13 Nov 2017
Learning to Draw Samples with Amortized Stein Variational Gradient Descent Yihao Feng Dilin Wang Qiang Liu GAN BDL 46 79 0 20 Jul 2017
A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum Wenkai Xu Z. Szabó Kenji Fukumizu Arthur Gretton 60 104 0 22 May 2017
Stein Variational Gradient Descent as Gradient Flow Qiang Liu OT 60 274 0 25 Apr 2017
Stein Variational Adaptive Importance Sampling J. Han Qiang Liu 46 28 0 18 Apr 2017
Stein Variational Policy Gradient Yang Liu Prajit Ramachandran Qiang Liu Jian-wei Peng 53 138 0 07 Apr 2017
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 116 223 0 06 Mar 2017
Reinforcement Learning with Deep Energy-Based Policies Tuomas Haarnoja Haoran Tang Pieter Abbeel Sergey Levine 62 1,329 0 27 Feb 2017
Measuring Sample Quality with Diffusions Jackson Gorham Andrew B. Duncan Sandra Jeanne Vollmer Lester W. Mackey 58 116 0 21 Nov 2016
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning Dilin Wang Qiang Liu GAN BDL 105 119 0 06 Nov 2016
Operator Variational Inference Rajesh Ranganath Jaan Altosaar Dustin Tran David M. Blei 38 116 0 27 Oct 2016
Black-box Importance Sampling Qiang Liu Jason D. Lee FAtt 36 74 0 17 Oct 2016
Bounds for the normal approximation of the maximum likelihood estimator from m-dependent random variables Andreas Anastasiou 26 22 0 19 Sep 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 61 1,082 0 16 Aug 2016
Convergence Rates for a Class of Estimators Based on Stein's Method Chris J. Oates Jon Cockayne F. Briol Mark Girolami 41 57 0 10 Mar 2016
A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation Qiang Liu Jason D. Lee Michael I. Jordan 94 478 0 10 Feb 2016
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann Arthur Gretton BDL 159 327 0 09 Feb 2016
Bounds for the asymptotic normality of the maximum likelihood estimator using the Delta method Andreas Anastasiou Christophe Ley 19 13 0 20 Aug 2015
Measuring Sample Quality with Stein's Method Jackson Gorham Lester W. Mackey 96 224 0 09 Jun 2015
Bounds for the normal approximation of the maximum likelihood estimator Andreas Anastasiou Gesine Reinert 21 11 0 10 Nov 2014
Stein's method for comparison of univariate distributions Christophe Ley Gesine Reinert Yvik Swan OT 50 149 0 13 Aug 2014
Parametric Stein operators and variance bounds Christophe Ley Yvik Swan 41 23 0 22 May 2013
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget Anoop Korattikara Yutian Chen Max Welling 60 243 0 19 Apr 2013
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring S. Ahn Anoop Korattikara Balan Max Welling 62 305 0 27 Jun 2012
Zero Variance Markov Chain Monte Carlo for Bayesian Estimators Antonietta Mira R. Solgi D. Imparato 66 89 0 14 Dec 2010
Stein couplings for normal approximation Louis H. Y. Chen Adrian Röllin 55 54 0 31 Mar 2010
Minimum Probability Flow Learning Jascha Narain Sohl-Dickstein P. Battaglino M. DeWeese 112 70 0 25 Jun 2009
A Kernel Method for the Two-Sample Problem Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alex Smola 169 2,352 0 15 May 2008