Understanding simple liquids through statistical and deep learning approaches
Author:
Affiliation:
1. Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
Funder
National Science Foundation
Publisher
AIP Publishing
Subject
Physical and Theoretical Chemistry,General Physics and Astronomy
Link
https://aip.scitation.org/doi/am-pdf/10.1063/5.0046226
Reference65 articles.
1. Transfer-Learning-Based Coarse-Graining Method for Simple Fluids: Toward Deep Inverse Liquid-State Theory
2. What Is a Simple Liquid?
3. Dynamic equivalences in the hard-sphere dynamic universality class
4. Explaining why simple liquids are quasi-universal
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