Showing 1–10 of 10 results
/ Date/ Name
May 2, 2025Multi-fidelity learning for interatomic potentials: Low-level forces and high-level energies are all you needApr 15, 2026Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic DataFeb 7, 2025Teacher-student training improves accuracy and efficiency of machine learning interatomic potentialsSep 13, 2025Reactive Chemistry at Unrestricted Coupled Cluster Level: High-throughput Calculations for Training Machine Learning PotentialsJun 11, 2025Going beyond density functional theory accuracy: Leveraging experimental data to refine pre-trained machine learning interatomic potentialsJul 8, 2023Learning Together: Towards foundational models for machine learning interatomic potentials with meta-learningJul 23, 2025Atomistic modeling of uranium monocarbide with a machine learning interatomic potentialNov 21, 2024Toward machine learning interatomic potentials for modeling uranium mononitrideMay 14, 2021Bayesian inference-driven model parameterization and model selection for 2CLJQ fluid modelsJul 10, 2023Machine learning potentials with Iterative Boltzmann Inversion: training to experiment