This work proposes PURE (Purging Unrelated Representations for Content-Agnostic Forgery Detection), which achieves content-agnostic detection through two complementary components: a Causal Semantic Generative (CSG) mechanism that disentangles semantic representations from forgery-irrelevant nuisance factors, and a Gaus...
Xin-Yu Wu, Dong Li, Minglai Shao et al.· Proceedings of the Thirty-Fi...· 0 citations
Identifying morphologically distinct cell populations in time-lapse fluorescence microscopy is central to understanding how complex tissues develop and remodel, yet remains labor-intensive and subject to observer bias despite advances in cell segmentation. We present a generalizable computational framework for automate...
Prateek Verma, Chloe A. Kuebler, Minh-Hao Van et al.· IEEE/ACM International Confe...· 0 citations
Spatial omics (SO) technologies enable spatially resolved molecular profiling, while hematoxylin and eosin (H&E) imaging remains the gold standard for morphological assessment in clinical pathology. Recent computational advances increasingly place H&E images at the center of SO analysis, bridging morphology with transc...
Ning-Hui Hao, Boshen Yan, Dong Li et al.· Proceedings of the 32nd ACM...· 0 citations
A message extrapolation mechanism under soft uncertainty constraints is proposed to obtain the diverse counterfactual message distributions and a novel robust representation learning framework for dynamic graph domain generalization, LEMD is proposed.
Xiaoran Wei, Chen Zhao, Minglai Shao et al.· 0 citations
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