15.4k citations · 15.8k across the 20 of their papers we have counts for
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Scalarization for Multi-Task and Multi-Domain Learning at Scale
Amelie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi
Training a single model on multiple input domains and/or output tasks allows for compressing information from multiple sources into a unified backbone hence improves model efficien…
MSViT: Dynamic Mixed-Scale Tokenization for Vision Transformers
Jakob Drachmann Havtorn, Amelie Royer, Tijmen Blankevoort +1
The input tokens to Vision Transformers carry little semantic meaning as they are defined as regular equal-sized patches of the input image, regardless of its content. However, pro…
Revisiting Single-gated Mixtures of Experts
Amelie Royer, Ilia Karmanov, Andrii Skliar +2
Mixture of Experts (MoE) are rising in popularity as a means to train extremely large-scale models, yet allowing for a reasonable computational cost at inference time. Recent state…
Computational Pathology: A Survey Review and The Way Forward
Mahdi S. Hosseini, Babak Ehteshami Bejnordi, Vincent Quoc-Huy Trinh +18
Computational Pathology CPath is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main ob…