1 code implementation • ICCV 2023 • Weiyi Wu, Chongyang Gao, Joseph DiPalma, Soroush Vosoughi, Saeed Hassanpour
This framework aims for transferable representation learning and semantically meaningful clustering by synergizing invariance loss and clustering loss in WSI analysis.
no code implementations • 11 Jan 2021 • Joseph DiPalma, Arief A. Suriawinata, Laura J. Tafe, Lorenzo Torresani, Saeed Hassanpour
Our results show that a combination of KD and self-supervision allows the student model to approach, and in some cases, surpass the classification accuracy of the teacher, while being much more efficient.
no code implementations • 13 Sep 2022 • Joseph DiPalma, Lorenzo Torresani, Saeed Hassanpour
These findings suggest that HistoPerm can be a valuable tool for improving representation learning of histopathology features when access to labeled data is limited and can lead to whole-slide classification results that are comparable to or superior to fully-supervised methods.