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20242026
most citedA Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications

12 citations · 23 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.LG2026

CARD: Coarse-to-fine Autoregressive Modeling with Radix-based Decomposition for Transferable Free Energy Estimation

Ziyang Yu, Yi He, Wenbing Huang +2

Estimating free energy differences quantifies thermodynamic preferences in molecular interactions, which is central to chemistry and drug discovery. Despite fruitful progress, exis…

cs.LG2026

Unified Biomolecular Trajectory Generation via Pretrained Variational Bridge

Ziyang Yu, Wenbing Huang, Yang Liu

Molecular Dynamics (MD) simulations provide a fundamental tool for characterizing molecular behavior at full atomic resolution, but their applicability is severely constrained by t…

cs.LG2025

Latent Retrieval Augmented Generation of Cross-Domain Protein Binders

Zishen Zhang, Xiangzhe Kong, Wenbing Huang +1

Designing protein binders targeting specific sites, which requires to generate realistic and functional interaction patterns, is a fundamental challenge in drug discovery. Current…

cs.LG2024★ 12 cited

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications

Jiaqi Han, Jiacheng Cen, Liming Wu +13

Geometric graphs are a special kind of graph with geometric features, which are vital to model many scientific problems. Unlike generic graphs, geometric graphs often exhibit physi…

cs.LG2024★ 1 cited

An Equivariant Pretrained Transformer for Unified 3D Molecular Representation Learning

Rui Jiao, Xiangzhe Kong, Li Zhang +5

Pretraining on a large number of unlabeled 3D molecules has showcased superiority in various scientific applications. However, prior efforts typically focus on pretraining models i…

cs.LG2024★ 5 cited

Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction

Ziyang Yu, Wenbing Huang, Yang Liu

The study of rigid protein-protein docking plays an essential role in a variety of tasks such as drug design and protein engineering. Recently, several learning-based methods have…