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cs.LG2024★ 1 cited
Bridging Geometric States via Geometric Diffusion Bridge
Shengjie Luo, Yixian Xu, Di He +3
The accurate prediction of geometric state evolution in complex systems is critical for advancing scientific domains such as quantum chemistry and material modeling. Traditional ex…
cs.LG2024
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning
Yuxuan Ren, Dihan Zheng, Chang Liu +7
In recent years, machine learning has demonstrated impressive capability in handling molecular science tasks. To support various molecular properties at scale, machine learning mod…
cs.LG2024
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
Tianlang Chen, Shengjie Luo, Di He +3
Molecular modeling, a central topic in quantum mechanics, aims to accurately calculate the properties and simulate the behaviors of molecular systems. The molecular model is govern…