9 papers
Project and Generate: Divergence-Free Neural Operators for Incompressible Flows
Xigui Li, Hongwei Zhang, Ruoxi Jiang +6
Learning-based models for fluid dynamics often operate in unconstrained function spaces, leading to physically inadmissible, unstable simulations. While penalty-based methods offer…
Rethinking Intracranial Aneurysm Vessel Segmentation: A Perspective from Computational Fluid Dynamics Applications
Feiyang Xiao, Yichi Zhang, Xigui Li +7
The precise segmentation of intracranial aneurysms and their parent vessels (IA-Vessel) is a critical step for hemodynamic analyses, which mainly depends on computational fluid dyn…
ChromFound: Towards A Universal Foundation Model for Single-Cell Chromatin Accessibility Data
Yifeng Jiao, Yuchen Liu, Yu Zhang +9
The advent of single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) offers an innovative perspective for deciphering regulatory mechanisms by assembl…
Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
Tan Pan, Kaiyu Guo, Dongli Xu +8
The generalization ability of deep learning has been extensively studied in supervised settings, yet it remains less explored in unsupervised scenarios. Recently, the Unsupervised…
Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification
Zhaorui Tan, Tan Pan, Kaizhu Huang +8
LayerNorm is pivotal in Vision Transformers (ViTs), yet its fine-tuning dynamics under data scarcity and domain shifts remain underexplored. This paper shows that shifts in LayerNo…
PAST: A multimodal single-cell foundation model for histopathology and spatial transcriptomics in cancer
Changchun Yang, Haoyang Li, Yushuai Wu +8
While pathology foundation models have transformed cancer image analysis, they often lack integration with molecular data at single-cell resolution, limiting their utility for prec…