3 citations · 4 across the 5 of their papers we have counts for
7 papers
Assay-Aware BindingDB: Curating Experimental Context for Binding Affinity Prediction
Ming-Hsiu Wu, Xuejiao Shirley Guo, Bingsong Zeng +5
Protein--ligand binding affinity prediction is fundamental to computational drug discovery, yet modern AI-driven models are limited by pervasive heterogeneity in their training dat…
AnaDiffusion: Anatomically Compositional Latent Diffusion for Controllable 3D Brain MRI Generation
Huiwen Han, Lulin Liu, Bangya Liu +8
3D brain MRI generation has made significant advances in medical imaging, simulation, and controllable anatomical analysis. However, existing generative models typically synthesize…
Towards Precision Protein-Ligand Affinity Prediction Benchmark: A Complete and Modification-Aware DAVIS Dataset
Ming-Hsiu Wu, Ziqian Xie, Shuiwang Ji +1
Advancements in AI for science unlocks capabilities for critical drug discovery tasks such as protein-ligand binding affinity prediction. However, current models overfit to existin…
EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association
Weiqi Wang, Limeng Cui, Xin Liu +14
Goal-oriented script planning, or the ability to devise coherent sequences of actions toward specific goals, is commonly employed by humans to plan for typical activities. In e-com…
Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning
Haoyu Han, Yaochen Xie, Hui Liu +8
Large language models (LLMs) have demonstrated remarkable success across a wide range of tasks; however, they still encounter challenges in reasoning tasks that require understandi…
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
Xuan Zhang, Jacob Helwig, Yuchao Lin +4
We consider using deep neural networks to solve time-dependent partial differential equations (PDEs), where multi-scale processing is crucial for modeling complex, time-evolving dy…
Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies
Yaochen Xie, Ziqian Xie, Sheikh Muhammad Saiful Islam +2
Genome-wide association studies (GWAS) are used to identify relationships between genetic variations and specific traits. When applied to high-dimensional medical imaging data, a k…