Understanding multi-fidelity training of machine-learned force-fields

Abstract This study systematically investigates two multi-fidelity strategies used to train machine-learned force fields (MLFFs)—pre-training/fine-tuning and multi-headed training—and elucidates the mechanisms underpinning their success. For pre-training and fine-tuning, we uncover a log–log linear ... View More