228 citations · 560 across the 25 of their papers we have counts for
3 papers · 1 filter
Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning
Richard J. Chen, Chengkuan Chen, Yicong Li +4
Vision Transformers (ViTs) and their multi-scale and hierarchical variations have been successful at capturing image representations but their use has been generally studied for lo…
Incorporating intratumoral heterogeneity into weakly-supervised deep learning models via variance pooling
Iain Carmichael, Andrew H. Song, Richard J. Chen +3
Supervised learning tasks such as cancer survival prediction from gigapixel whole slide images (WSIs) are a critical challenge in computational pathology that requires modeling com…
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology
Richard J. Chen, Rahul G. Krishnan
Tissue phenotyping is a fundamental task in learning objective characterizations of histopathologic biomarkers within the tumor-immune microenvironment in cancer pathology. However…