2023
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
NeurIPS 2023poster
Interatomic potentials learned using machine learning methods have been successfully applied to atomistic simulations. However, accurate models require large training datasets, while generating reference calculations is computationally demanding. To bypass this difficulty, we propose a transfer lea…