Lifelong Machine Learning Potentials

10 March 2023

Papers citing "Lifelong Machine Learning Potentials"

3 / 3 papers shown

Title
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance Raphael T. Husistein Markus Reiher Marco Eckhoff 115 1 0 20 Feb 2025
FeNNol: an Efficient and Flexible Library for Building Force-field-enhanced Neural Network Potentials Thomas Plé Olivier Adjoua Louis Lagardère Jean‐Philip Piquemal 27 8 0 02 May 2024
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 142 244 0 01 May 2021