From Optimization to Sampling Through Gradient Flows

22 February 2023

Papers citing "From Optimization to Sampling Through Gradient Flows"

9 / 9 papers shown

Title
Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 74 7 0 25 Jun 2024
A Fisher-Rao gradient flow for entropic mean-field min-max games Razvan-Andrei Lascu Mateusz B. Majka Lukasz Szpruch MLT AI4CE 112 3 0 24 May 2024
Sequential-in-time training of nonlinear parametrizations for solving time-dependent partial differential equations Huan Zhang Yifan Chen Eric Vanden-Eijnden Benjamin Peherstorfer 69 3 0 01 Apr 2024
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities Rocco Caprio Juan Kuntz Samuel Power A. M. Johansen 90 10 0 04 Mar 2024
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints Lingkai Kong Yuanqi Du Wenhao Mu Kirill Neklyudov Valentin De Bortol ... D. Wu Aaron Ferber Yi-An Ma Carla P. Gomes Chao Zhang 80 13 0 28 Feb 2024
Sampling in Unit Time with Kernel Fisher-Rao Flow A. Maurais Youssef Marzouk 69 18 0 08 Jan 2024
Sampling via Gradient Flows in the Space of Probability Measures Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 66 15 0 05 Oct 2023
Generative Sliced MMD Flows with Riesz Kernels J. Hertrich Christian Wald Fabian Altekrüger Paul Hagemann 97 27 0 19 May 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 65 19 0 21 Feb 2023