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
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
The Causal-Neural Connection: Expressiveness, Learnability, and Inference K. Xia Kai-Zhan Lee Yoshua Bengio Elias Bareinboim CML 20 104 0 02 Jul 2021
Three rates of convergence or separation via U-statistics in a dependent framework Quentin Duchemin Yohann De Castro C. Lacour 8 0 0 24 Jun 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
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 51 93 0 22 Jun 2021
Non Gaussian Denoising Diffusion Models Eliya Nachmani Robin San Roman Lior Wolf VLM DiffM 32 48 0 14 Jun 2021
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics Carles Domingo-Enrich Youssef Mroueh 21 1 0 10 Jun 2021
Detecting Anomalous Event Sequences with Temporal Point Processes Oleksandr Shchur Ali Caner Turkmen Tim Januschowski Jan Gasthaus Stephan Günnemann AI4TS 20 12 0 08 Jun 2021
Instrument Space Selection for Kernel Maximum Moment Restriction Rui Zhang Krikamol Muandet Bernhard Schölkopf Masaaki Imaizumi 14 3 0 07 Jun 2021
Stein ICP for Uncertainty Estimation in Point Cloud Matching F. A. Maken Fabio Ramos Lionel Ott 3DV 3DPC 26 25 0 07 Jun 2021
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1 Adil Salim Lukang Sun Peter Richtárik 23 20 0 06 Jun 2021
Efficient and Generalizable Tuning Strategies for Stochastic Gradient MCMC Jeremie Coullon Leah F. South Christopher Nemeth 11 12 0 27 May 2021
Statistical Depth Meets Machine Learning: Kernel Mean Embeddings and Depth in Functional Data Analysis George Wynne Stanislav Nagy 11 5 0 26 May 2021
Kernel Stein Discrepancy Descent Anna Korba Pierre-Cyril Aubin-Frankowski Szymon Majewski Pierre Ablin 16 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 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 19 9 0 15 Apr 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 24 74 0 15 Apr 2021
Noise Estimation for Generative Diffusion Models Robin San-Roman Eliya Nachmani Lior Wolf DiffM 28 105 0 06 Apr 2021
Post-Processing of MCMC Leah F. South M. Riabiz Onur Teymur Chris J. Oates 22 17 0 30 Mar 2021
Posterior Meta-Replay for Continual Learning Christian Henning Maria R. Cervera Francesco DÁngelo J. Oswald Regina Traber Benjamin Ehret Seijin Kobayashi Benjamin Grewe João Sacramento CLL BDL 51 54 0 01 Mar 2021
A Stein Goodness of fit Test for Exponential Random Graph Models Wenkai Xu Gesine Reinert 21 5 0 28 Feb 2021
Stein Variational Gradient Descent: many-particle and long-time asymptotics Nikolas Nusken D. M. Renger 27 22 0 25 Feb 2021
Product-form estimators: exploiting independence to scale up Monte Carlo Juan Kuntz F. R. Crucinio A. M. Johansen 28 10 0 23 Feb 2021
Tractable Computation of Expected Kernels Wenzhe Li Zhe Zeng Antonio Vergari Guy Van den Broeck TPM 18 1 0 21 Feb 2021
Active Slices for Sliced Stein Discrepancy Wenbo Gong Kaibo Zhang Yingzhen Li José Miguel Hernández-Lobato 22 8 0 05 Feb 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 104 185 0 12 Jan 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 24 241 0 09 Jan 2021
Integrable Nonparametric Flows David Pfau Danilo Jimenez Rezende 6 5 0 03 Dec 2020
Diffusion models for Handwriting Generation Troy Luhman Eric Luhman DiffM 19 25 0 13 Nov 2020
Dimension-agnostic inference using cross U-statistics Ilmun Kim Aaditya Ramdas 19 16 0 10 Nov 2020
Characterizations of non-normalized discrete probability distributions and their application in statistics Steffen Betsch B. Ebner F. Nestmann 11 13 0 09 Nov 2020
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 31 15 0 22 Oct 2020
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models Fan Bao Kun Xu Chongxuan Li Lanqing Hong Jun Zhu Bo Zhang DiffM 22 8 0 16 Oct 2020
Auxiliary Task Reweighting for Minimum-data Learning Baifeng Shi Judy Hoffman Kate Saenko Trevor Darrell Huijuan Xu MoMe 27 32 0 16 Oct 2020
Testing for Normality with Neural Networks M. Simic 19 6 0 29 Sep 2020
Stein Variational Gaussian Processes Thomas Pinder Christopher Nemeth David Leslie BDL 6 7 0 25 Sep 2020
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent Rahif Kassab Osvaldo Simeone FedML 23 45 0 11 Sep 2020
Blindness of score-based methods to isolated components and mixing proportions Wenliang K. Li Heishiro Kanagawa 17 34 0 23 Aug 2020
Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data T. Fernandez Nicolás Rivera Wenkai Xu A. Gretton 6 15 0 19 Aug 2020
Learning Gradient Fields for Shape Generation Ruojin Cai Guandao Yang Hadar Averbuch-Elor Jinwei Gu Serge J. Belongie Noah Snavely B. Hariharan 3DPC 19 280 0 14 Aug 2020
Fisher Auto-Encoders Khalil Elkhalil Ali Hasan Jie Ding Sina Farsiu Vahid Tarokh 9 9 0 12 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching Tianyu Pang Kun Xu Chongxuan Li Yang Song Stefano Ermon Jun Zhu DiffM 31 53 0 07 Jul 2020
Kernel Stein Generative Modeling Wei-Cheng Chang Chun-Liang Li Youssef Mroueh Yiming Yang DiffM BDL 35 5 0 06 Jul 2020
Stochastic Stein Discrepancies Jackson Gorham Anant Raj Lester W. Mackey 19 37 0 06 Jul 2020
Sliced Kernelized Stein Discrepancy Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato 20 37 0 30 Jun 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
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization Shijing Si Chris J. Oates Andrew B. Duncan Lawrence Carin F. Briol BDL 15 21 0 12 Jun 2020