12 citations · 23 across the 10 of their papers we have counts for
11 papers
Continuous-Time Quantum Walks based Graph Neural Network
Yuliang Zhan, Zefeng Gao, Jian Li +2
Graph Neural Networks (GNNs) are widely used on graph-structured data, but most suffer from two key weaknesses. First, message passing behaves as a low-pass filter under the homoph…
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…
CloDS: Visual-Only Unsupervised Cloth Dynamics Learning in Unknown Conditions
Yuliang Zhan, Jian Li, Wenbing Huang +2
Deep learning has demonstrated remarkable capabilities in simulating complex dynamic systems. However, existing methods require known physical properties as supervision or inputs,…
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…
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…
UniSim: A Unified Simulator for Time-Coarsened Dynamics of Biomolecules
Ziyang Yu, Wenbing Huang, Yang Liu
Molecular Dynamics (MD) simulations are essential for understanding the atomic-level behavior of molecular systems, giving insights into their transitions and interactions. However…
Force-Guided Bridge Matching for Full-Atom Time-Coarsened Dynamics of Peptides
Ziyang Yu, Wenbing Huang, Yang Liu
Molecular Dynamics (MD) is crucial in various fields such as materials science, chemistry, and pharmacology to name a few. Conventional MD software struggles with the balance betwe…
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…
Full-Atom Peptide Design with Geometric Latent Diffusion
Xiangzhe Kong, Yinjun Jia, Wenbing Huang +1
Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to leverage target binding sites that are previously undruggable. Most existing methods are eith…
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…
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…