Contrastive Regularization of Machine Learning Potentials

Dimitrios Tzivrailis, Georgios Sotiropoulos, Alberto Rosso +1

Machine learning models are increasingly trained as regressors and then deployed as generators, from language models to learned simulators. In this setting, accuracy on held-out da…