3 citations · 4 across the 3 of their papers we have counts for
3 papers
Elucidating the Design Space of Flow Matching for Cellular Microscopy
Charles Jones, Emmanuel Noutahi, Jason Hartford +1
Flow-matching generative models are increasingly used to simulate cell responses to biological perturbations. However, the design space for building such models is large and undere…
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models
Konstantin Donhauser, Kristina Ulicna, Gemma Elyse Moran +4
Sparse dictionary learning (DL) has emerged as a powerful approach to extract semantically meaningful concepts from the internals of large language models (LLMs) trained mainly in…
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik +10
Large-scale cell microscopy screens are used in drug discovery and molecular biology research to study the effects of millions of chemical and genetic perturbations on cells. To us…