activity
20202026
most citedExtending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms

41 citations · 70 across the 9 of their papers we have counts for

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2 papers · 1 filter

cs.LG2026

Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning

Chen Wang, Siyu Hu, Guangming Tan +1

SO(3) equivariant graph neural networks have become the dominant paradigm for atomistic foundation models, achieving high accuracy and data efficiency by building rotational symmet…

cs.LG2026

MatRIS: Toward Reliable and Efficient Pretrained Machine Learning Interatomic Potentials

Yuanchang Zhou, Siyu Hu, Xiangyu Zhang +3

Foundation MLIPs demonstrate broad applicability across diverse material systems and have emerged as a powerful and transformative paradigm in chemical and computational materials…