Projected Wasserstein gradient descent for high-dimensional Bayesian
inference

Projected Wasserstein gradient descent for high-dimensional Bayesian inference

12 February 2021

Wuchen Li

Papers citing "Projected Wasserstein gradient descent for high-dimensional Bayesian inference"

10 / 10 papers shown

Title
The Score-Difference Flow for Implicit Generative Modeling Romann M. Weber DiffM 29 2 0 25 Apr 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space Michael Diao Krishnakumar Balasubramanian Sinho Chewi Adil Salim BDL 21 20 0 10 Apr 2023
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 11 17 0 21 Feb 2023
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 24 19 0 25 Nov 2022
Efficient Gradient Flows in Sliced-Wasserstein Space Clément Bonet Nicolas Courty Franccois Septier Lucas Drumetz 29 21 0 21 Oct 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 46 93 0 22 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 40 52 0 01 Jun 2021
Projected Stein Variational Gradient Descent Peng Chen Omar Ghattas BDL 55 68 0 09 Feb 2020
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 185 3,262 0 09 Jun 2012