2 citations · 2 across the 2 of their papers we have counts for
8 papers
Pretraining a Foundation Model for Small-Molecule Natural Products
Yuheng Ding, Bo Qiang, Shaoning Li +8
Natural products, as metabolites from microorganisms, animals, or plants, exhibit diverse biological activities, making them crucial for drug discovery. Nowadays, existing deep lea…
Riemannian Consistency Model
Chaoran Cheng, Yusong Wang, Yuxin Chen +3
Consistency models are a class of generative models that enable few-step generation for diffusion and flow matching models. While consistency models have achieved promising results…
MCGM: Multi-stage Clustered Global Modeling for Long-range Interactions in Molecules
Haodong Pan, Yusong Wang, Nanning Zheng +1
Geometric graph neural networks (GNNs) excel at capturing molecular geometry, yet their locality-biased message passing hampers the modeling of long-range interactions. Current sol…
Neural PM: A Long-Range Interaction Modeling Enhancer for Geometric GNNs
Yusong Wang, Chaoran Cheng, Shaoning Li +5
Geometric graph neural networks (GNNs) have emerged as powerful tools for modeling molecular geometry. However, they encounter limitations in effectively capturing long-range inter…
Improving AlphaFlow for Efficient Protein Ensembles Generation
Shaoning Li, Mingyu Li, Yusong Wang +4
Investigating conformational landscapes of proteins is a crucial way to understand their biological functions and properties. AlphaFlow stands out as a sequence-conditioned generat…
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
He Zhang, Chang Liu, Zun Wang +5
Predicting the mean-field Hamiltonian matrix in density functional theory is a fundamental formulation to leverage machine learning for solving molecular science problems. Yet, its…