Path-Gradient Estimators for Continuous Normalizing Flows

17 June 2022

Papers citing "Path-Gradient Estimators for Continuous Normalizing Flows"

9 / 9 papers shown

Title
Fast and Unified Path Gradient Estimators for Normalizing Flows Lorenz Vaitl Ludwig Winkler Lorenz Richter Pan Kessel 31 4 0 23 Mar 2024
Multi-Lattice Sampling of Quantum Field Theories via Neural Operator-based Flows Bálint Máté Franccois Fleuret AI4CE 31 0 0 01 Jan 2024
Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows Mingxuan Yi Song Liu DRL 20 8 0 31 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization Dinghuai Zhang Ricky Tian Qi Chen Cheng-Hao Liu Aaron C. Courville Yoshua Bengio 34 40 0 04 Oct 2023
Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics Kyle Cranmer G. Kanwar S. Racanière Danilo Jimenez Rezende P. Shanahan AI4CE 29 27 0 03 Sep 2023
Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows M. Caselle E. Cellini A. Nada 20 14 0 03 Jul 2023
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 56 24 0 17 Jul 2022
Learning Lattice Quantum Field Theories with Equivariant Continuous Flows Mathis Gerdes P. D. Haan Corrado Rainone Roberto Bondesan Miranda C. N. Cheng AI4CE 16 40 0 01 Jul 2022
On the Difficulty of Unbiased Alpha Divergence Minimization Tomas Geffner Justin Domke 55 18 0 19 Oct 2020