3 papers
cs.CV2026
Mixture of Mini Experts: Overcoming the Linear Layer Bottleneck in Multiple Instance Learning
Daniel Shao, Joel Runevic, Richard J. Chen +4
Multiple Instance Learning (MIL) is the predominant framework for classifying gigapixel whole-slide images in computational pathology. MIL follows a sequence of 1) extracting patch…
cs.CV2025
Do Multiple Instance Learning Models Transfer?
Daniel Shao, Richard J. Chen, Andrew H. Song +4
Multiple Instance Learning (MIL) is a cornerstone approach in computational pathology (CPath) for generating clinically meaningful slide-level embeddings from gigapixel tissue imag…
cs.CV2025
A Foundation Model for Spatial Proteomics
Muhammad Shaban, Yuzhou Chang, Huaying Qiu +57
Foundation models have begun to transform image analysis by acting as pretrained generalist backbones that can be adapted to many tasks even when post-training data are limited, ye…