Search Results for author:
Found 3 papers, 2 papers with code
Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space
Molecular dynamics (MD) is a powerful tool for exploring the behavior of atomistic systems, but its reliance on sequential numerical integration limits simulation efficiency.
Physics-informed active learning for accelerating quantum chemical simulations
Quantum chemical simulations can be greatly accelerated by constructing machine learning potentials, which is often done using active learning (AL).
MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows
MLatom 3 is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
