A Kernel Test of Goodness of Fit

9 February 2016

Kacper P. Chwialkowski

Papers citing "A Kernel Test of Goodness of Fit"

50 / 95 papers shown

Title
A Dictionary of Closed-Form Kernel Mean Embeddings F. Briol A. Gessner Toni Karvonen Maren Mahsereci BDL 90 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 74 0 0 13 Mar 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 79 0 0 25 Feb 2025
Stein Discrepancy for Unsupervised Domain Adaptation Anneke von Seeger Dongmian Zou Gilad Lerman 104 0 0 24 Feb 2025
Empirical Bayes Estimation with Side Information: A Nonparametric Integrative Tweedie Approach Jiajun Luo Trambak Banerjee Gourab Mukherjee Wenguang Sun 83 0 0 17 Feb 2025
Recurrent Neural Goodness-of-Fit Test for Time Series Aoran Zhang Wenbin Zhou Liyan Xie Shixiang Zhu 45 1 0 17 Oct 2024
Sequential Kernelized Stein Discrepancy Diego Martinez-Taboada Aaditya Ramdas 57 0 0 26 Sep 2024
On the Robustness of Kernel Goodness-of-Fit Tests Xing Liu F. Briol OOD 86 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 48 5 0 06 Aug 2024
Nyström Kernel Stein Discrepancy Florian Kalinke Zoltan Szabo Bharath K. Sriperumbudur 60 1 0 12 Jun 2024
Diffusion Models for Generating Ballistic Spacecraft Trajectories Tyler Presser Agnimitra Dasgupta Daniel Erwin Assad A. Oberai DiffM 57 3 0 20 May 2024
Data-centric Prediction Explanation via Kernelized Stein Discrepancy Mahtab Sarvmaili Hassan Sajjad Ga Wu 41 1 0 22 Mar 2024
Mean-field underdamped Langevin dynamics and its spacetime discretization Qiang Fu Ashia Wilson 54 4 0 26 Dec 2023
CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems Christian L. Jacobsen Yilin Zhuang Karthik Duraisamy AI4CE SyDa DiffM 44 19 0 16 Dec 2023
Spectral Regularized Kernel Goodness-of-Fit Tests Omar Hagrass Bharath K. Sriperumbudur Bing Li 45 3 0 08 Aug 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 54 7 0 27 May 2023
Learning Rate Free Sampling in Constrained Domains Louis Sharrock Lester W. Mackey Christopher Nemeth 51 2 0 24 May 2023
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent Tianle Liu Promit Ghosal Krishnakumar Balasubramanian Natesh S. Pillai 59 9 0 23 May 2023
Kernel Stein Discrepancy on Lie Groups: Theory and Applications Xiaoda Qu Xiran Fan B. Vemuri 46 0 0 21 May 2023
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 53 7 0 01 Dec 2022
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 36 19 0 25 Nov 2022
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent Jiaxin Shi Lester W. Mackey 33 18 0 17 Nov 2022
Minimum Kernel Discrepancy Estimators Chris J. Oates 39 10 0 28 Oct 2022
MARS: Meta-Learning as Score Matching in the Function Space Krunoslav Lehman Pavasovic Jonas Rothfuss Andreas Krause BDL 55 4 0 24 Oct 2022
A kernel Stein test of goodness of fit for sequential models Jerome Baum Heishiro Kanagawa Arthur Gretton 46 9 0 19 Oct 2022
Variance-Aware Estimation of Kernel Mean Embedding Geoffrey Wolfer Pierre Alquier 40 4 0 13 Oct 2022
Auto-Encoding Goodness of Fit A. Palmer Zhiyi Chi Derek Aguiar J. Bi 51 1 0 12 Oct 2022
On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics Moritz Weckbecker Wenkai Xu Gesine Reinert 55 3 0 11 Oct 2022
How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences Mikolaj Kasprzak Ryan Giordano Tamara Broderick 38 4 0 29 Sep 2022
Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp Carl-Johann Simon-Gabriel Mark Girolami Lester W. Mackey 68 14 0 26 Sep 2022
Learning to Increase the Power of Conditional Randomization Tests Shalev Shaer Yaniv Romano CML 45 2 0 03 Jul 2022
Stein Variational Goal Generation for adaptive Exploration in Multi-Goal Reinforcement Learning Nicolas Castanet Sylvain Lamprier Olivier Sigaud 25 3 0 14 Jun 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 41 4 0 09 Jun 2022
MixFlows: principled variational inference via mixed flows Zuheng Xu Na Chen Trevor Campbell 68 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 43 25 0 20 Mar 2022
AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators Wenkai Xu Gesine Reinert 42 4 0 07 Mar 2022
Stein Particle Filter for Nonlinear, Non-Gaussian State Estimation F. A. Maken Fabio Ramos Lionel Ott 37 19 0 09 Feb 2022
Grassmann Stein Variational Gradient Descent Xingtu Liu Harrison Zhu Jean-François Ton George Wynne Andrew Duncan 51 12 0 07 Feb 2022
Kernel Two-Sample Tests in High Dimension: Interplay Between Moment Discrepancy and Dimension-and-Sample Orders J. Yan Xianyang Zhang 57 17 0 31 Dec 2021
Bounding Wasserstein distance with couplings N. Biswas Lester W. Mackey 40 8 0 06 Dec 2021
Composite Goodness-of-fit Tests with Kernels Oscar Key Arthur Gretton F. Briol T. Fernandez 43 14 0 19 Nov 2021
A Computationally Efficient Method for Learning Exponential Family Distributions Abhin Shah Devavrat Shah G. Wornell 37 10 0 28 Oct 2021
MMD Aggregated Two-Sample Test Antonin Schrab Ilmun Kim Mélisande Albert Béatrice Laurent Benjamin Guedj Arthur Gretton 40 56 0 28 Oct 2021
Generalized Kernel Thinning Raaz Dwivedi Lester W. Mackey 45 29 0 04 Oct 2021
Minimum Discrepancy Methods in Uncertainty Quantification Chris J. Oates 54 2 0 13 Sep 2021
A Survey of Monte Carlo Methods for Parameter Estimation D. Luengo Luca Martino M. Bugallo Victor Elvira S. Särkkä 37 154 0 25 Jul 2021
Interpreting diffusion score matching using normalizing flow Wenbo Gong Yingzhen Li DiffM 41 13 0 21 Jul 2021
Sampling with Mirrored Stein Operators Jiaxin Shi Chang-rui Liu Lester W. Mackey 56 19 0 23 Jun 2021
Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fit Wenkai Xu 41 4 0 23 Jun 2021
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1 Adil Salim Lukang Sun Peter Richtárik 33 20 0 06 Jun 2021