Fine-tuning ML interatomic potentials via a new LoRA-based Equitrain framework with minimal additional data improves phonon and thermal predictions over base and scratch-trained models in 53 systems.
Accelerating high-throughput phonon calculations via machine learn- ing universal potentials
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Parameter-Efficient Fine-Tuning of Machine-Learning Interatomic Potentials for Phonon and Thermal Properties
Fine-tuning ML interatomic potentials via a new LoRA-based Equitrain framework with minimal additional data improves phonon and thermal predictions over base and scratch-trained models in 53 systems.