Stein Variational Gradient Descent With Matrix-Valued Kernels

28 October 2019

Papers citing "Stein Variational Gradient Descent With Matrix-Valued Kernels"

22 / 22 papers shown

Title
Taming High-Dimensional Dynamics: Learning Optimal Projections onto Spectral Submanifolds Hugo Buurmeijer Luis A. Pabon J. I. Alora Roshan S. Kaundinya George Haller Marco Pavone 31 0 0 04 Apr 2025
ELBOing Stein: Variational Bayes with Stein Mixture Inference Ola Rønning Eric T. Nalisnick Christophe Ley Padhraic Smyth Thomas Hamelryck BDL 50 1 0 30 Oct 2024
Stein Variational Evolution Strategies Cornelius V. Braun Robert T. Lange Marc Toussaint 26 0 0 14 Oct 2024
Electrostatics-based particle sampling and approximate inference Yongchao Huang DiffM 29 2 0 28 Jun 2024
Stein Random Feature Regression Houston Warren Rafael Oliveira Fabio Ramos BDL 36 0 0 01 Jun 2024
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes J. Hauth C. Safta Xun Huan Ravi G. Patel Reese E. Jones BDL UQCV 25 2 0 17 Feb 2024
Convergence and stability results for the particle system in the Stein gradient descent method José A. Carrillo Jakub Skrzeczkowski 17 2 0 26 Dec 2023
Noise-Free Sampling Algorithms via Regularized Wasserstein Proximals Hongwei Tan Stanley Osher Wuchen Li 24 7 0 28 Aug 2023
Constrained Stein Variational Trajectory Optimization Thomas Power Dmitry Berenson 28 12 0 23 Aug 2023
Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models Terrence Alsup Tucker Hartland Benjamin Peherstorfer N. Petra 11 1 0 06 Dec 2022
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 22 19 0 25 Nov 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 21 19 0 01 Jun 2022
Stein Variational Probabilistic Roadmaps Alexander Lambert Brian Hou Rosario Scalise S. Srinivasa Byron Boots 11 8 0 04 Nov 2021
Stein Variational Gradient Descent with Multiple Kernel Qingzhong Ai Shiyu Liu Lirong He Zenglin Xu 11 4 0 20 Jul 2021
Entropy Regularized Motion Planning via Stein Variational Inference Alexander Lambert Byron Boots 37 12 0 11 Jul 2021
Sampling with Mirrored Stein Operators Jiaxin Shi Chang-rui Liu Lester W. Mackey 39 19 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 G. Reinert Yvik Swan 22 35 0 07 May 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 19 74 0 15 Apr 2021
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence Sinho Chewi Thibaut Le Gouic Chen Lu Tyler Maunu Philippe Rigollet 18 66 0 03 Jun 2020
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 191 498 0 11 Jun 2018
A Stein variational Newton method Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl 61 114 0 08 Jun 2018
MCMC using Hamiltonian dynamics Radford M. Neal 182 3,262 0 09 Jun 2012