From the 2 of 4 linked papers with an AI index.
4 papers
APO: Unsupervised Atomic Policy Optimization for 3D Structure Prediction of Atomic Systems
Shentong Mo, Yatao Bian
The paper introduces Atomic Policy Optimization (APO), an unsupervised method that learns to predict 3D structures of atomic systems by optimizing a policy with dual rewards for st…
Advancing Optimal Subset Oracle via Learning Relaxation of Neural Set Functions
Yongquan Shi, Zijing Ou, Shiping Wang +1
The paper proposes a continuous relaxation of neural set functions that replaces Monte‑Carlo gradient estimation in optimal subset oracle training with a learned surrogate objectiv…
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking
Yiqiang Yi, Xu Wan, Yatao Bian +2
Predicting the docking between proteins and ligands is a crucial and challenging task for drug discovery. However, traditional docking methods mainly rely on scoring functions, and…
InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
Yifan Niu, Ziqi Gao, Tingyang Xu +5
Exploring chemical space to find novel molecules that simultaneously satisfy multiple properties is crucial in drug discovery. However, existing methods often struggle with trading…