most citedOptimizing Cross-Domain Transfer for Universal Machine Learning Interatomic Potentials

3 citations · 3 across the 1 of their papers we have counts for

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1 paper

cond-mat.mtrl-sci2025★ 3 cited

Optimizing Cross-Domain Transfer for Universal Machine Learning Interatomic Potentials

Jaesun Kim, Jinmu You, Yutack Park +11

Accurate yet transferable machine-learning interatomic potentials (MLIPs) are essential for accelerating materials and chemical discovery. However, most universal MLIPs overfit to…