A Riemann-Stein Kernel Method

11 October 2018

Papers citing "A Riemann-Stein Kernel Method"

41 / 41 papers shown

Title
Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp Carl-Johann Simon-Gabriel Mark Girolami Lester W. Mackey 96 15 0 26 Sep 2022
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 79 15 0 22 Oct 2020
Optimal quantisation of probability measures using maximum mean discrepancy Onur Teymur Jackson Gorham M. Riabiz Chris J. Oates 61 29 0 14 Oct 2020
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization Shijing Si Chris J. Oates Andrew B. Duncan Lawrence Carin F. Briol BDL 50 21 0 12 Jun 2020
Optimal Thinning of MCMC Output M. Riabiz W. Chen Jon Cockayne P. Swietach Steven Niederer Lester W. Mackey Chris J. Oates 62 47 0 08 May 2020
A diffusion approach to Stein's method on Riemannian manifolds Huiling Le Alexander Lewis Karthik Bharath C. Fallaize OT 28 11 0 25 Mar 2020
Semi-Exact Control Functionals From Sard's Method Leah F. South Toni Karvonen Christopher Nemeth Mark Girolami Chris J. Oates 36 17 0 31 Jan 2020
The reproducing Stein kernel approach for post-hoc corrected sampling Liam Hodgkinson R. Salomone Fred Roosta 65 27 0 25 Jan 2020
Variance reduction for Markov chains with application to MCMC Denis Belomestny L. Iosipoi Eric Moulines A. Naumov S. Samsonov BDL 46 30 0 08 Oct 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim Arthur Gretton 103 163 0 11 Jun 2019
Reproducing kernel Hilbert spaces on manifolds: Sobolev and Diffusion spaces Ernesto De Vito Nicole Mücke Lorenzo Rosasco 36 27 0 27 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 73 57 0 09 May 2019
Irreversible Langevin MCMC on Lie Groups Alexis Arnaudon Alessandro Barp So Takao AI4CE 32 5 0 21 Mar 2019
Hamiltonian Monte Carlo on Symmetric and Homogeneous Spaces via Symplectic Reduction Alessandro Barp A. Kennedy Mark Girolami 27 9 0 07 Mar 2019
A weighted Discrepancy Bound of quasi-Monte Carlo Importance Sampling J. Dick Daniel Rudolf Hou-Ying Zhu 25 10 0 21 Jan 2019
Stein Variational Gradient Descent Without Gradient J. Han Qiang Liu 81 45 0 07 Jun 2018
Neural Control Variates for Variance Reduction Ruosi Wan Mingjun Zhong Haoyi Xiong Zhanxing Zhu BDL DRL 57 18 0 01 Jun 2018
Regularized Finite Dimensional Kernel Sobolev Discrepancy Youssef Mroueh 18 4 0 16 May 2018
Stein Points W. Chen Lester W. Mackey Jackson Gorham François‐Xavier Briol Chris J. Oates 60 102 0 27 Mar 2018
Intrinsic Gaussian processes on complex constrained domains Mu Niu P. Cheung Lizhen Lin Zhenwen Dai Neil D. Lawrence David B. Dunson 58 41 0 03 Jan 2018
Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs V. R. Joseph Dianpeng Wang Li Gu Shiji Lyu Rui Tuo 25 36 0 24 Dec 2017
Riemannian Stein Variational Gradient Descent for Bayesian Inference Chang-rui Liu Jun Zhu 55 67 0 30 Nov 2017
Sobolev GAN Youssef Mroueh Chun-Liang Li Tom Sercu Anant Raj Yu Cheng 45 117 0 14 Nov 2017
Message Passing Stein Variational Gradient Descent Jingwei Zhuo Chang-rui Liu Jiaxin Shi Jun Zhu Ning Chen Bo Zhang 54 92 0 13 Nov 2017
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 118 223 0 06 Mar 2017
Geodesic Lagrangian Monte Carlo over the space of positive definite matrices: with application to Bayesian spectral density estimation Andrew J Holbrook Shiwei Lan A. Vandenberg-Rodes Babak Shahbaba 48 26 0 24 Dec 2016
Black-box Importance Sampling Qiang Liu Jason D. Lee FAtt 59 74 0 17 Oct 2016
Support points Simon Mak V. R. Joseph 49 139 0 07 Sep 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 68 1,092 0 16 Aug 2016
Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions Carl-Johann Simon-Gabriel Bernhard Schölkopf 49 92 0 18 Apr 2016
Convergence Rates for a Class of Estimators Based on Stein's Method Chris J. Oates Jon Cockayne F. Briol Mark Girolami 48 57 0 10 Mar 2016
A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation Qiang Liu Jason D. Lee Michael I. Jordan 100 483 0 10 Feb 2016
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann Arthur Gretton BDL 198 328 0 09 Feb 2016
Stein's method for comparison of univariate distributions Christophe Ley Gesine Reinert Yvik Swan OT 75 149 0 13 Aug 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 452 16,933 0 20 Dec 2013
Spherical Hamiltonian Monte Carlo for Constrained Target Distributions Shiwei Lan Bo Zhou Babak Shahbaba 82 58 0 17 Sep 2013
Geodesic Monte Carlo on Embedded Manifolds Simon Byrne Mark Girolami 96 152 0 25 Jan 2013
Sampling From A Manifold P. Diaconis Susan P. Holmes M. Shahshahani 89 116 0 28 Jun 2012
Strictly and non-strictly positive definite functions on spheres T. Gneiting 154 320 0 30 Nov 2011
Zero Variance Markov Chain Monte Carlo for Bayesian Estimators Antonietta Mira R. Solgi D. Imparato 91 89 0 14 Dec 2010
Universality, Characteristic Kernels and RKHS Embedding of Measures Bharath K. Sriperumbudur Kenji Fukumizu Gert R. G. Lanckriet 216 530 0 03 Mar 2010