SVGD as a kernelized Wasserstein gradient flow of the chi-squared
divergence

SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence

3 June 2020

Thibaut Le Gouic

Philippe Rigollet

Papers citing "SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence"

19 / 19 papers shown

Title
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime Raphael Barboni Gabriel Peyré François-Xavier Vialard MLT 34 0 0 25 Apr 2025
Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals Alexander Mielke Jia Jie Zhu 58 1 0 28 Jan 2025
ELBOing Stein: Variational Bayes with Stein Mixture Inference Ola Rønning Eric T. Nalisnick Christophe Ley Padhraic Smyth Thomas Hamelryck BDL 52 1 0 30 Oct 2024
MESSY Estimation: Maximum-Entropy based Stochastic and Symbolic densitY Estimation Tony Tohme Mohsen Sadr K. Youcef-Toumi N. Hadjiconstantinou 30 3 0 07 Jun 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 25 7 0 27 May 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space Michael Diao Krishnakumar Balasubramanian Sinho Chewi Adil Salim BDL 15 20 0 10 Apr 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
Improving Task-free Continual Learning by Distributionally Robust Memory Evolution Zhenyi Wang Li Shen Le Fang Qiuling Suo Tiehang Duan Mingchen Gao OOD 22 38 0 15 Jul 2022
An Accelerated Stochastic Algorithm for Solving the Optimal Transport Problem Yiling Xie Yiling Luo X. Huo 14 10 0 02 Mar 2022
A blob method for inhomogeneous diffusion with applications to multi-agent control and sampling Katy Craig Karthik Elamvazhuthi M. Haberland O. Turanova 25 15 0 25 Feb 2022
Kernel Stein Discrepancy Descent Anna Korba Pierre-Cyril Aubin-Frankowski Szymon Majewski Pierre Ablin 13 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 G. Reinert Yvik Swan 22 35 0 07 May 2021
Sampling From the Wasserstein Barycenter Chiheb Daaloul Thibaut Le Gouic J. Liandrat M. I. O. Technology 11 6 0 04 May 2021
Multilevel Stein variational gradient descent with applications to Bayesian inverse problems Terrence Alsup Luca Venturi Benjamin Peherstorfer 11 5 0 05 Apr 2021
Stein Variational Gradient Descent: many-particle and long-time asymptotics Nikolas Nusken D. M. Renger 19 22 0 25 Feb 2021
Random Coordinate Langevin Monte Carlo Zhiyan Ding Qin Li Jianfeng Lu Stephen J. Wright BDL 10 11 0 03 Oct 2020
A Stein variational Newton method Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl 61 114 0 08 Jun 2018
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 127 1,198 0 16 Aug 2016