CellBridge is introduced, a multi-modal contrastive learning framework pretrained on 16M cells with paired H&E and spatial profiles, for transferring molecular information into morphological representations that consistently achieves smaller prediction sets, while reducing class-wise coverage gaps.
This paper proposes a methodology for crafting principled frequency-based adversarial attacks, via a dedicated optimization framework, and proves that the attacks emerge as weighted $\ell_2$-projections onto this set, yielding a general and controlled attack generation mechanism.
Vicky Kouni, Stelios Perrakis, Francis R. Bach et al.· 0 citations
ProtScape, a multiscale graph-learning framework integrating global protein interactions, cell-type gene expression and protein language models to learn context-specific representations and infer interactomes across more than 200 cell types, substantially outperforms existing approaches in interaction reconstruction.
Alois Thomas, Lisa Fournier, Vincent Jung et al.· bioRxiv· 0 citations
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