A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation

10 February 2016

Papers citing "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation"

50 / 296 papers shown

Title
Constrained Stein Variational Trajectory Optimization Thomas Power Dmitry Berenson 33 12 0 23 Aug 2023
Semi-Implicit Variational Inference via Score Matching Longlin Yu C. Zhang 19 10 0 19 Aug 2023
Spectral Regularized Kernel Goodness-of-Fit Tests Omar Hagrass Bharath K. Sriperumbudur Bing Li 29 3 0 08 Aug 2023
Energy Discrepancies: A Score-Independent Loss for Energy-Based Models Tobias Schröder Zijing Ou Jen Ning Lim Yingzhen Li Sebastian J. Vollmer Andrew B. Duncan 30 4 0 12 Jul 2023
A prior regularized full waveform inversion using generative diffusion models Fu Wang Xinquan Huang T. Alkhalifah DiffM 40 25 0 22 Jun 2023
MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting Felix Biggs Antonin Schrab A. Gretton 17 19 0 14 Jun 2023
Convergence of mean-field Langevin dynamics: Time and space discretization, stochastic gradient, and variance reduction Taiji Suzuki Denny Wu Atsushi Nitanda 29 16 0 12 Jun 2023
Entropy-based Training Methods for Scalable Neural Implicit Sampler Weijian Luo Boya Zhang Zhihua Zhang 31 10 0 08 Jun 2023
GANs Settle Scores! Siddarth Asokan Nishanth Shetty Aadithya Srikanth C. Seelamantula 42 0 0 02 Jun 2023
Approximate Stein Classes for Truncated Density Estimation Daniel J. Williams Song Liu 13 0 0 01 Jun 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 35 7 0 27 May 2023
Non-adversarial training of Neural SDEs with signature kernel scores Zacharia Issa Blanka Horvath M. Lemercier C. Salvi AI4TS 37 24 0 25 May 2023
Learning Rate Free Sampling in Constrained Domains Louis Sharrock Lester W. Mackey Christopher Nemeth 38 2 0 24 May 2023
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent Tianle Liu Promit Ghosal Krishnakumar Balasubramanian Natesh S. Pillai 27 9 0 23 May 2023
Kernel Stein Discrepancy on Lie Groups: Theory and Applications Xiaoda Qu Xiran Fan B. Vemuri 32 0 0 21 May 2023
Stein $Π$ -Importance Sampling Congye Wang Ye Chen Heishiro Kanagawa Chris J. Oates 37 2 0 17 May 2023
Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang 50 3 0 01 May 2023
Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy Xingtu Liu Andrew B. Duncan Axel Gandy 35 7 0 28 Apr 2023
The Score-Difference Flow for Implicit Generative Modeling Romann M. Weber DiffM 29 2 0 25 Apr 2023
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise Francesco Montagna Nicoletta Noceti Lorenzo Rosasco Anton van den Hengel Francesco Locatello CML 13 27 0 06 Apr 2023
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks Forough Fazeli Asl M. Zhang Lizhen Lin 24 1 0 05 Mar 2023
How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control Jacopo Teneggi Matthew Tivnan J. W. Stayman Jeremias Sulam DiffM 35 28 0 07 Feb 2023
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization Clément Bénard B. Staber Sébastien Da Veiga 38 4 0 31 Jan 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
Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models Dat Do Huy Nguyen Khai Nguyen Nhat Ho 23 4 0 27 Jan 2023
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates Louis Sharrock Christopher Nemeth BDL 28 8 0 26 Jan 2023
Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation Shahar Lutati Eliya Nachmani Lior Wolf DiffM 36 14 0 25 Jan 2023
Client Selection for Federated Bayesian Learning Jiarong Yang Yuan Liu Rahif Kassab FedML 38 11 0 11 Dec 2022
Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning Yingchun Wang Song Guo Jingcai Guo Weizhan Zhang Yi Tian Xu Jiewei Zhang Yi Liu 21 17 0 07 Dec 2022
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 32 7 0 01 Dec 2022
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 27 19 0 25 Nov 2022
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent Jiaxin Shi Lester W. Mackey 28 18 0 17 Nov 2022
Sobolev Spaces, Kernels and Discrepancies over Hyperspheres S. Hubbert Emilio Porcu Chris J. Oates Mark Girolami 11 4 0 16 Nov 2022
Regularized Stein Variational Gradient Flow Ye He Krishnakumar Balasubramanian Bharath K. Sriperumbudur Jianfeng Lu OT 34 11 0 15 Nov 2022
Aspects of scaling and scalability for flow-based sampling of lattice QCD Ryan Abbott M. S. Albergo Aleksandar Botev D. Boyda Kyle Cranmer ... Ali Razavi Danilo Jimenez Rezende F. Romero-López P. Shanahan Julian M. Urban 32 33 0 14 Nov 2022
Controlling Moments with Kernel Stein Discrepancies Heishiro Kanagawa Alessandro Barp A. Gretton Lester W. Mackey 24 8 0 10 Nov 2022
Ensemble transport smoothing. Part II: Nonlinear updates M. Ramgraber Ricardo Baptista D. McLaughlin Youssef Marzouk 23 6 0 31 Oct 2022
Minimum Kernel Discrepancy Estimators Chris J. Oates 27 10 0 28 Oct 2022
Preferential Subsampling for Stochastic Gradient Langevin Dynamics Srshti Putcha Christopher Nemeth Paul Fearnhead 22 0 0 28 Oct 2022
MARS: Meta-Learning as Score Matching in the Function Space Krunoslav Lehman Pavasovic Jonas Rothfuss Andreas Krause BDL 30 4 0 24 Oct 2022
A kernel Stein test of goodness of fit for sequential models Jerome Baum Heishiro Kanagawa A. Gretton 24 9 0 19 Oct 2022
Transport Elliptical Slice Sampling A. Cabezas Christopher Nemeth 16 8 0 19 Oct 2022
Auto-Encoding Goodness of Fit A. Palmer Zhiyi Chi Derek Aguiar J. Bi 41 1 0 12 Oct 2022
On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics Moritz Weckbecker Wenkai Xu Gesine Reinert 52 3 0 11 Oct 2022
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models Louis Sharrock J. Simons Song Liu Mark Beaumont DiffM 61 33 0 10 Oct 2022
Hiding Images in Deep Probabilistic Models Haoyu Chen Linqi Song Zhenxing Qian Xinpeng Zhang Kede Ma AAML 18 10 0 05 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
Amortized Variational Inference: A Systematic Review Ankush Ganguly Sanjana Jain Ukrit Watchareeruetai 25 14 0 22 Sep 2022
Towards Healing the Blindness of Score Matching Mingtian Zhang Oscar Key Peter Hayes David Barber Brooks Paige F. Briol MedIm 55 14 0 15 Sep 2022