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cs.CV2025★ 4 cited
Distilling foundation models for robust and efficient models in digital pathology
Alexandre Filiot, Nicolas Dop, Oussama Tchita +8
In recent years, the advent of foundation models (FM) for digital pathology has relied heavily on scaling the pre-training datasets and the model size, yielding large and powerful…
cs.CV2024
Transcriptomics-guided Slide Representation Learning in Computational Pathology
Guillaume Jaume, Lukas Oldenburg, Anurag Vaidya +5
Self-supervised learning (SSL) has been successful in building patch embeddings of small histology images (e.g., 224x224 pixels), but scaling these models to learn slide embeddings…