Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion

29 January 2020

Papers citing "Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion"

4 / 4 papers shown

Title
SetPINNs: Set-based Physics-informed Neural Networks M. Nagda Phil Ostheimer Thomas Specht Frank Rhein F. Jirasek Stephan Mandt Marius Kloft Sophie Fellenz 3DPC PINN 46 0 0 30 Sep 2024
Gibbs-Helmholtz Graph Neural Network: capturing the temperature dependency of activity coefficients at infinite dilution E. Medina S. Linke Martin Stoll K. Sundmacher 30 11 0 02 Dec 2022
A smile is all you need: Predicting limiting activity coefficients from SMILES with natural language processing Benedikt Winter Clemens Winter J. Schilling A. Bardow 25 28 0 15 Jun 2022
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 232 503 0 20 Oct 2020