Measuring Sample Quality with Stein's Method

9 June 2015

Papers citing "Measuring Sample Quality with Stein's Method"

50 / 62 papers shown

Title
Stein Discrepancy for Unsupervised Domain Adaptation Anneke von Seeger Dongmian Zou Gilad Lerman 92 0 0 24 Feb 2025
Sequential Kernelized Stein Discrepancy Diego Martinez-Taboada Aaditya Ramdas 38 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
Nyström Kernel Stein Discrepancy Florian Kalinke Zoltan Szabo Bharath K. Sriperumbudur 46 1 0 12 Jun 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 62 1 0 31 May 2024
Touring sampling with pushforward maps Vivien A. Cabannes Charles Arnal 26 0 0 23 Nov 2023
Gibbs Sampling the Posterior of Neural Networks Giovanni Piccioli Emanuele Troiani Lenka Zdeborová 41 2 0 05 Jun 2023
Kernel Stein Discrepancy on Lie Groups: Theory and Applications Xiaoda Qu Xiran Fan B. Vemuri 32 0 0 21 May 2023
The Score-Difference Flow for Implicit Generative Modeling Romann M. Weber DiffM 29 2 0 25 Apr 2023
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 24 7 0 28 Jan 2023
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner Julija Zavadlav 35 21 0 15 Dec 2022
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 34 7 0 01 Dec 2022
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent Jiaxin Shi Lester W. Mackey 28 18 0 17 Nov 2022
A kernel Stein test of goodness of fit for sequential models Jerome Baum Heishiro Kanagawa A. Gretton 24 9 0 19 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 33 4 0 29 Sep 2022
Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp Carl-Johann Simon-Gabriel Mark Girolami Lester W. Mackey 48 14 0 26 Sep 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
AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators Wenkai Xu Gesine Reinert 32 4 0 07 Mar 2022
Bounding Wasserstein distance with couplings N. Biswas Lester W. Mackey 30 8 0 06 Dec 2021
Composite Goodness-of-fit Tests with Kernels Oscar Key A. Gretton F. Briol T. Fernandez 30 14 0 19 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 41 13 0 03 Nov 2021
Generalized Kernel Thinning Raaz Dwivedi Lester W. Mackey 36 29 0 04 Oct 2021
Minimum Discrepancy Methods in Uncertainty Quantification Chris J. Oates 39 2 0 13 Sep 2021
A Survey of Monte Carlo Methods for Parameter Estimation D. Luengo Luca Martino M. Bugallo Victor Elvira S. Särkkä 21 153 0 25 Jul 2021
Interpreting diffusion score matching using normalizing flow Wenbo Gong Yingzhen Li DiffM 27 13 0 21 Jul 2021
Stein Variational Gradient Descent with Multiple Kernel Qingzhong Ai Shiyu Liu Lirong He Zenglin Xu 22 4 0 20 Jul 2021
Sampling with Mirrored Stein Operators Jiaxin Shi Chang-rui Liu Lester W. Mackey 45 19 0 23 Jun 2021
Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fit Wenkai Xu 32 4 0 23 Jun 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 22 35 0 07 May 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 22 17 0 06 May 2021
On Energy-Based Models with Overparametrized Shallow Neural Networks Carles Domingo-Enrich A. Bietti Eric Vanden-Eijnden Joan Bruna BDL 33 9 0 15 Apr 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 27 74 0 15 Apr 2021
Post-Processing of MCMC Leah F. South M. Riabiz Onur Teymur Chris J. Oates 22 17 0 30 Mar 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 24 241 0 09 Jan 2021
Blindness of score-based methods to isolated components and mixing proportions Wenliang K. Li Heishiro Kanagawa 17 34 0 23 Aug 2020
Nonparametric Score Estimators Yuhao Zhou Jiaxin Shi Jun Zhu 32 23 0 20 May 2020
Mutual Information Gradient Estimation for Representation Learning Liangjiang Wen Yiji Zhou Lirong He Mingyuan Zhou Zenglin Xu DRL SSL 25 27 0 03 May 2020
Convergence diagnostics for Markov chain Monte Carlo Vivekananda Roy 21 217 0 26 Sep 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 22 134 0 16 Jul 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 43 397 0 25 Jun 2019
Minimum Stein Discrepancy Estimators Alessandro Barp François‐Xavier Briol Andrew B. Duncan Mark Girolami Lester W. Mackey 33 90 0 19 Jun 2019
Estimating Convergence of Markov chains with L-Lag Couplings N. Biswas Pierre E. Jacob Paul Vanetti 27 47 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 35 56 0 09 May 2019
The Born Supremacy: Quantum Advantage and Training of an Ising Born Machine Brian Coyle Daniel Mills V. Danos E. Kashefi 27 155 0 03 Apr 2019
Random Feature Stein Discrepancies Jonathan H. Huggins Lester W. Mackey 35 45 0 20 Jun 2018
A Spectral Approach to Gradient Estimation for Implicit Distributions Jiaxin Shi Shengyang Sun Jun Zhu 17 90 0 07 Jun 2018
Sobolev Descent Youssef Mroueh Tom Sercu Anant Raj OT 21 1 0 30 May 2018
Fisher Efficient Inference of Intractable Models Song Liu Takafumi Kanamori Wittawat Jitkrittum Yu Chen 29 14 0 18 May 2018
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms Marco F. Cusumano-Towner Vikash K. Mansinghka 8 17 0 19 May 2017