Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with
a Kernel Approach

Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach

4 May 2020

Frank Noè

Papers citing "Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach"

5 / 5 papers shown

Title
Machine Learning Coarse-Grained Potentials of Protein Thermodynamics Maciej Majewski Adriana Pérez Philipp Thölke Stefan Doerr N. Charron T. Giorgino B. Husic C. Clementi Frank Noé Gianni De Fabritiis AI4CE 30 70 0 14 Dec 2022
Automatic Identification of Chemical Moieties Jonas Lederer M. Gastegger Kristof T. Schütt Michael C. Kampffmeyer Klaus-Robert Muller Oliver T. Unke 28 5 0 30 Mar 2022
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 34 891 0 14 Oct 2020
Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties Benjamin Kurt Miller Mario Geiger Tess E. Smidt Frank Noé 21 75 0 19 Aug 2020
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics C. Wehmeyer Frank Noé AI4CE BDL 111 357 0 30 Oct 2017