25 citations · 30 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 25 cited
A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems
Shuo Zhang, Yang Liu, Lei Xie
Molecular sciences address a wide range of problems involving molecules of different types and sizes and their complexes. Recently, geometric deep learning, especially Graph Neural…
q-bio.QM2022★ 5 cited
Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs
Rui Jiao, Jiaqi Han, Wenbing Huang +2
Pretraining molecular representation models without labels is fundamental to various applications. Conventional methods mainly process 2D molecular graphs and focus solely on 2D ta…