5 papers
WaveFormer: Frequency-Time Decoupled Vision Modeling with Wave Equation
Zishan Shu, Juntong Wu, Wei Yan +5
Vision modeling has advanced rapidly with Transformers, whose attention mechanisms capture visual dependencies but lack a principled account of how semantic information propagates…
Pseudodata-guided Invariant Representation Learning Boosts the Out-of-Distribution Generalization in Enzymatic Kinetic Parameter Prediction
Haomin Wu, Zhiwei Nie, Hongyu Zhang +1
Accurate prediction of enzyme kinetic parameters is essential for understanding catalytic mechanisms and guiding enzyme engineering.However, existing deep learning-based enzyme-sub…
Comp-Attn: Present-and-Align Attention for Compositional Video Generation
Hongyu Zhang, Yufan Deng, Shenghai Yuan +5
In the domain of text-to-video (T2V) generation, reliably synthesizing compositional content involving multiple subjects with intricate relations is still underexplored. The main c…
OmniESI: A unified framework for enzyme-substrate interaction prediction with progressive conditional deep learning
Zhiwei Nie, Hongyu Zhang, Hao Jiang +8
Understanding and modeling enzyme-substrate interactions is crucial for catalytic mechanism research, enzyme engineering, and metabolic engineering. Although a large number of pred…
MTPNet: Multi-Grained Target Perception for Unified Activity Cliff Prediction
Zishan Shu, Yufan Deng, Hongyu Zhang +2
Activity cliff prediction is a critical task in drug discovery and material design. Existing computational methods are limited to handling single binding targets, which restricts t…