Work

Predicting rare events using neural networks and short-trajectory data

Year: 2023

Type: article

Source: Journal of Computational Physics

DOI: 10.1016/j.jcp.2023.112152

Authors: John Strahan, Justin Finkel, Aaron R. Dinner, Jonathan Weare

Institutions: University of Chicago, Massachusetts Institute of Technology, Courant Institute of Mathematical Sciences, New York University

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: bronze

Funders: National Science Foundation, U.S. Department of Energy, University of Chicago, Climate Extremes, National Institutes of Health, Office of Science, National Institute of General Medical Sciences, Advanced Scientific Computing Research

Awards: DMS/NIGMS 1: Design and Analysis of Machine Learning Approaches for Long Timescale Prediction from Short Trajectory Data, Rare-event simulation and analysis for elucidating mechanisms of development and disease, DOE COMPUTATIONAL SCIENCE GRADUATE FELLOWSHIP (CSGF) GRANT 2019 COHORT, DOE COMPUTATIONAL SCIENCE GRADUATE FELLOWSHIP (CSGF) GRANT 2019 COHORT

OpenAlex ID: W4375948460

FWCI: 2.59

Cites: 70

Cited by: 27

Related to: 10