4 papers
A Large-Scale Benchmark of Cross-Modal Learning for Histology and Gene Expression in Spatial Transcriptomics
Rushin H. Gindra, Giovanni Palla, Mathias Nguyen +6
Spatial transcriptomics enables simultaneous measurement of gene expression and tissue morphology, offering unprecedented insights into cellular organization and disease mechanisms…
B-Cos Aligned Transformers Learn Human-Interpretable Features
Manuel Tran, Amal Lahiani, Yashin Dicente Cid +7
Vision Transformers (ViTs) and Swin Transformers (Swin) are currently state-of-the-art in computational pathology. However, domain experts are still reluctant to use these models d…
Training Transitive and Commutative Multimodal Transformers with LoReTTa
Manuel Tran, Yashin Dicente Cid, Amal Lahiani +3
Training multimodal foundation models is challenging due to the limited availability of multimodal datasets. While many public datasets pair images with text, few combine images wi…
S5CL: Unifying Fully-Supervised, Self-Supervised, and Semi-Supervised Learning Through Hierarchical Contrastive Learning
Manuel Tran, Sophia J. Wagner, Melanie Boxberg +1
In computational pathology, we often face a scarcity of annotations and a large amount of unlabeled data. One method for dealing with this is semi-supervised learning which is comm…