Active Learning for Machine-Learned Potentials

Advisor: Dr. Zachary Ulissi

Time: Aug’20 - Dec’20

Source Code: Github Repository

Lead developer of al_mlp, an active learning package for conducting Δ-machine learning to learn the correction between a simple physics-based potential and an expensive ab-initio level theory.