A Kernel Test of Goodness of Fit

9 February 2016

Kacper P. Chwialkowski

Papers citing "A Kernel Test of Goodness of Fit"

45 / 95 papers shown

Title
Kernel Stein Discrepancy Descent Anna Korba Pierre-Cyril Aubin-Frankowski Szymon Majewski Pierre Ablin 26 50 0 20 May 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 36 35 0 07 May 2021
On Energy-Based Models with Overparametrized Shallow Neural Networks Carles Domingo-Enrich A. Bietti Eric Vanden-Eijnden Joan Bruna BDL 42 9 0 15 Apr 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 32 75 0 15 Apr 2021
Post-Processing of MCMC Leah F. South M. Riabiz Onur Teymur Chris J. Oates 34 18 0 30 Mar 2021
Stein Variational Gradient Descent: many-particle and long-time asymptotics Nikolas Nusken D. M. Renger 53 22 0 25 Feb 2021
Two-sample Test with Kernel Projected Wasserstein Distance Jie Wang Rui Gao Yao Xie 31 19 0 12 Feb 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 106 187 0 12 Jan 2021
Characterizations of non-normalized discrete probability distributions and their application in statistics Steffen Betsch B. Ebner F. Nestmann 41 13 0 09 Nov 2020
Two-sample Test using Projected Wasserstein Distance Jie Wang Rui Gao Yao Xie 37 19 0 22 Oct 2020
Testing for Normality with Neural Networks M. Simic 29 6 0 29 Sep 2020
Blindness of score-based methods to isolated components and mixing proportions Wenliang K. Li Heishiro Kanagawa 36 34 0 23 Aug 2020
Stochastic Stein Discrepancies Jackson Gorham Anant Raj Lester W. Mackey 35 37 0 06 Jul 2020
A Non-Asymptotic Analysis for Stein Variational Gradient Descent Anna Korba Adil Salim Michael Arbel Giulia Luise Arthur Gretton 29 76 0 17 Jun 2020
Nonparametric Score Estimators Yuhao Zhou Jiaxin Shi Jun Zhu 40 23 0 20 May 2020
Optimal Thinning of MCMC Output M. Riabiz W. Chen Jon Cockayne P. Swietach Steven Niederer Lester W. Mackey Chris J. Oates 29 45 0 08 May 2020
Distributionally Robust Bayesian Optimization Johannes Kirschner Ilija Bogunovic Stefanie Jegelka Andreas Krause 45 77 0 20 Feb 2020
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings Junhyung Park Krikamol Muandet 37 78 0 10 Feb 2020
The reproducing Stein kernel approach for post-hoc corrected sampling Liam Hodgkinson R. Salomone Fred Roosta 45 27 0 25 Jan 2020
A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family Trambak Banerjee Qiang Liu Gourab Mukherjee Wengunag Sun 34 7 0 20 Oct 2019
Minimum Stein Discrepancy Estimators Alessandro Barp François‐Xavier Briol Andrew B. Duncan Mark Girolami Lester W. Mackey 38 91 0 19 Jun 2019
A Kernel Loss for Solving the Bellman Equation Yihao Feng Lihong Li Qiang Liu 30 70 0 25 May 2019
Estimating Convergence of Markov chains with L-Lag Couplings N. Biswas Pierre E. Jacob Paul Vanetti 32 48 0 23 May 2019
Stein Point Markov Chain Monte Carlo W. Chen Alessandro Barp François‐Xavier Briol Jackson Gorham Mark Girolami Lester W. Mackey Chris J. Oates 49 56 0 09 May 2019
Stein Variational Gradient Descent as Moment Matching Qiang Liu Dilin Wang 44 37 0 27 Oct 2018
Signature moments to characterize laws of stochastic processes I. Chevyrev Harald Oberhauser 24 108 0 25 Oct 2018
High-dimensional Varying Index Coefficient Models via Stein's Identity Sen Na Zhuoran Yang Zhaoran Wang Mladen Kolar 29 21 0 16 Oct 2018
Random Feature Stein Discrepancies Jonathan H. Huggins Lester W. Mackey 46 45 0 20 Jun 2018
A Spectral Approach to Gradient Estimation for Implicit Distributions Jiaxin Shi Shengyang Sun Jun Zhu 35 90 0 07 Jun 2018
Stein Variational Gradient Descent Without Gradient J. Han Qiang Liu 38 45 0 07 Jun 2018
Sobolev Descent Youssef Mroueh Tom Sercu Anant Raj OT 26 1 0 30 May 2018
Fisher Efficient Inference of Intractable Models Song Liu Takafumi Kanamori Wittawat Jitkrittum Yu Chen 42 14 0 18 May 2018
Stein Points W. Chen Lester W. Mackey Jackson Gorham François‐Xavier Briol Chris J. Oates 26 101 0 27 Mar 2018
Characteristic and Universal Tensor Product Kernels Z. Szabó Bharath K. Sriperumbudur 41 72 0 28 Aug 2017
A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum Wenkai Xu Z. Szabó Kenji Fukumizu Arthur Gretton 31 103 0 22 May 2017
Gradient Estimators for Implicit Models Yingzhen Li Richard Turner 35 104 0 19 May 2017
Stein Variational Gradient Descent as Gradient Flow Qiang Liu OT 36 272 0 25 Apr 2017
Stein Variational Adaptive Importance Sampling J. Han Qiang Liu 29 28 0 18 Apr 2017
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 86 223 0 06 Mar 2017
Two Methods For Wild Variational Inference Qiang Liu Yihao Feng BDL 32 19 0 30 Nov 2016
Measuring Sample Quality with Diffusions Jackson Gorham Andrew B. Duncan Sandra Jeanne Vollmer Lester W. Mackey 43 116 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
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 26 1,074 0 16 Aug 2016
A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation Qiang Liu Jason D. Lee Michael I. Jordan 68 476 0 10 Feb 2016
Measuring Sample Quality with Stein's Method Jackson Gorham Lester W. Mackey 62 223 0 09 Jun 2015