Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths

28 January 2025

Papers citing "Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths"

10 / 10 papers shown

Title
Deep adaptive sampling for surrogate modeling without labeled data Xili Wang Keju Tang Jiayu Zhai Xiaoliang Wan Chao Yang 47 2 0 17 Feb 2024
Adaptive deep density approximation for Fokker-Planck equations Keju Tang Xiaoliang Wan Qifeng Liao 60 37 0 20 Mar 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 268 6,293 0 26 Nov 2020
VAE-KRnet and its applications to variational Bayes Xiaoliang Wan Shuangqing Wei BDL DRL 42 13 0 29 Jun 2020
Computing Committor Functions for the Study of Rare Events Using Deep Learning Qianxiao Li Bo Lin W. Ren 43 67 0 14 Jun 2019
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 212 3,110 0 09 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 232 5,024 0 19 Jun 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 115 9,312 0 09 Feb 2018
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems E. Weinan Ting Yu 100 1,373 0 30 Sep 2017
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 185 3,681 0 26 May 2016