A Kernel Test of Goodness of Fit

9 February 2016

Kacper P. Chwialkowski

Papers citing "A Kernel Test of Goodness of Fit"

50 / 67 papers shown

Title
A Dictionary of Closed-Form Kernel Mean Embeddings F. Briol A. Gessner Toni Karvonen Maren Mahsereci BDL 75 1 0 26 Apr 2025
Improving Diffusion-based Inverse Algorithms under Few-Step Constraint via Learnable Linear Extrapolation Jiawei Zhang Ziyuan Liu Leon Yan Gen Li Yuantao Gu 54 0 0 13 Mar 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 75 0 0 25 Feb 2025
Stein Discrepancy for Unsupervised Domain Adaptation Anneke von Seeger Dongmian Zou Gilad Lerman 89 0 0 24 Feb 2025
Empirical Bayes Estimation with Side Information: A Nonparametric Integrative Tweedie Approach Jiajun Luo Trambak Banerjee Gourab Mukherjee Wenguang Sun 68 0 0 17 Feb 2025
Recurrent Neural Goodness-of-Fit Test for Time Series Aoran Zhang Wenbin Zhou Liyan Xie Shixiang Zhu 32 1 0 17 Oct 2024
Sequential Kernelized Stein Discrepancy Diego Martinez-Taboada Aaditya Ramdas 35 0 0 26 Sep 2024
On the Robustness of Kernel Goodness-of-Fit Tests Xing Liu F. Briol OOD 75 4 0 11 Aug 2024
Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator Xinghao Dong Chuanqi Chen Jin-Long Wu DiffM AI4CE 41 5 0 06 Aug 2024
Nyström Kernel Stein Discrepancy Florian Kalinke Zoltan Szabo Bharath K. Sriperumbudur 41 1 0 12 Jun 2024
Diffusion Models for Generating Ballistic Spacecraft Trajectories Tyler Presser Agnimitra Dasgupta Daniel Erwin Assad A. Oberai DiffM 34 3 0 20 May 2024
Mean-field underdamped Langevin dynamics and its spacetime discretization Qiang Fu Ashia Wilson 32 4 0 26 Dec 2023
Spectral Regularized Kernel Goodness-of-Fit Tests Omar Hagrass Bharath K. Sriperumbudur Bing Li 24 3 0 08 Aug 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 25 7 0 27 May 2023
Kernel Stein Discrepancy on Lie Groups: Theory and Applications Xiaoda Qu Xiran Fan B. Vemuri 29 0 0 21 May 2023
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 24 7 0 01 Dec 2022
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
Minimum Kernel Discrepancy Estimators Chris J. Oates 22 10 0 28 Oct 2022
MARS: Meta-Learning as Score Matching in the Function Space Krunoslav Lehman Pavasovic Jonas Rothfuss Andreas Krause BDL 23 4 0 24 Oct 2022
A kernel Stein test of goodness of fit for sequential models Jerome Baum Heishiro Kanagawa A. Gretton 18 9 0 19 Oct 2022
Variance-Aware Estimation of Kernel Mean Embedding Geoffrey Wolfer Pierre Alquier 19 4 0 13 Oct 2022
Auto-Encoding Goodness of Fit A. Palmer Zhiyi Chi Derek Aguiar J. Bi 27 1 0 12 Oct 2022
On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics Moritz Weckbecker Wenkai Xu G. Reinert 47 3 0 11 Oct 2022
Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp Carl-Johann Simon-Gabriel Mark Girolami Lester W. Mackey 40 14 0 26 Sep 2022
Learning to Increase the Power of Conditional Randomization Tests Shalev Shaer Yaniv Romano CML 24 2 0 03 Jul 2022
A Fourier representation of kernel Stein discrepancy with application to Goodness-of-Fit tests for measures on infinite dimensional Hilbert spaces George Wynne Mikolaj Kasprzak Andrew B. Duncan 25 4 0 09 Jun 2022
MixFlows: principled variational inference via mixed flows Zuheng Xu Na Chen Trevor Campbell 55 8 0 16 May 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents Alessandro Barp Lancelot Da Costa G. Francca Karl J. Friston Mark Girolami Michael I. Jordan G. Pavliotis 28 25 0 20 Mar 2022
Stein Particle Filter for Nonlinear, Non-Gaussian State Estimation F. A. Maken Fabio Ramos Lionel Ott 21 19 0 09 Feb 2022
Grassmann Stein Variational Gradient Descent Xingtu Liu Harrison Zhu Jean-François Ton George Wynne Andrew Duncan 21 12 0 07 Feb 2022
Bounding Wasserstein distance with couplings N. Biswas Lester W. Mackey 15 8 0 06 Dec 2021
Composite Goodness-of-fit Tests with Kernels Oscar Key A. Gretton F. Briol T. Fernandez 24 14 0 19 Nov 2021
A Computationally Efficient Method for Learning Exponential Family Distributions Abhin Shah Devavrat Shah G. Wornell 20 9 0 28 Oct 2021
Generalized Kernel Thinning Raaz Dwivedi Lester W. Mackey 36 29 0 04 Oct 2021
Minimum Discrepancy Methods in Uncertainty Quantification Chris J. Oates 23 2 0 13 Sep 2021
A Survey of Monte Carlo Methods for Parameter Estimation D. Luengo Luca Martino M. Bugallo Victor Elvira S. Särkkä 14 153 0 25 Jul 2021
Interpreting diffusion score matching using normalizing flow Wenbo Gong Yingzhen Li DiffM 17 13 0 21 Jul 2021
Sampling with Mirrored Stein Operators Jiaxin Shi Chang-rui Liu Lester W. Mackey 42 19 0 23 Jun 2021
Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fit Wenkai Xu 29 4 0 23 Jun 2021
Kernel Stein Discrepancy Descent Anna Korba Pierre-Cyril Aubin-Frankowski Szymon Majewski Pierre Ablin 13 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 G. Reinert Yvik Swan 22 35 0 07 May 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 19 74 0 15 Apr 2021
Stein Variational Gradient Descent: many-particle and long-time asymptotics Nikolas Nusken D. M. Renger 16 22 0 25 Feb 2021
Two-sample Test with Kernel Projected Wasserstein Distance Jie Wang Rui Gao Yao Xie 14 19 0 12 Feb 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 101 184 0 12 Jan 2021
Testing for Normality with Neural Networks M. Simic 11 6 0 29 Sep 2020
Blindness of score-based methods to isolated components and mixing proportions Wenliang K. Li Heishiro Kanagawa 13 34 0 23 Aug 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
Nonparametric Score Estimators Yuhao Zhou Jiaxin Shi Jun Zhu 22 23 0 20 May 2020