8 papers
A Semi-supervised Molecular Learning Framework for Activity Cliff Estimation
Fang Wu
Machine learning (ML) enables accurate and fast molecular property predictions, which are of interest in drug discovery and material design. Their success is based on the principle…
FieldSeer I: Physics-Guided World Models for Long-Horizon Electromagnetic Dynamics under Partial Observability
Ziheng Guo, Fang Wu, Maoxiong Zhao +2
We introduce FieldSeer I, a geometry-aware world model that forecasts electromagnetic field dynamics from partial observations in 2-D TE waveguides. The model assimilates a short p…
Joint Design of Protein Surface and Structure Using a Diffusion Bridge Model
Guanlue Li, Xufeng Zhao, Fang Wu +1
Protein-protein interactions (PPIs) are governed by surface complementarity and hydrophobic interactions at protein interfaces. However, designing diverse and physically realistic…
RiboPO: Preference Optimization for Structure- and Stability-Aware RNA Design
Minghao Sun, Hanqun Cao, Zhou Zhang +10
Designing RNA sequences that reliably adopt specified three-dimensional structures while maintaining thermodynamic stability remains challenging for synthetic biology and therapeut…
CEPerFed: Communication-Efficient Personalized Federated Learning for Multi-Pulse MRI Classification
Ludi Li, Junbin Mao, Hanhe Lin +3
Multi-pulse magnetic resonance imaging (MRI) is widely utilized for clinical practice such as Alzheimer's disease diagnosis. To train a robust model for multi-pulse MRI classificat…
From Supervision to Exploration: What Does Protein Language Model Learn During Reinforcement Learning?
Hanqun Cao, Hongrui Zhang, Junde Xu +12
Protein language models (PLMs) have advanced computational protein science through large-scale pretraining and scalable architectures. In parallel, reinforcement learning (RL) has…