10 papers
Conditional Neural Optimal Transport for Predicting Cellular Phenotypes from Molecular Structure
Gauthier Avité, Maxime Sanchez-Renauld, Nicolas Bourriez +1
High-content microscopy enables systematic profiling of cellular responses to chemical perturbations, but the scale of the chemical space makes exhaustive phenotypic characterizati…
XFACTORS: Disentangled Information Bottleneck via Contrastive Supervision
Alexandre Myara, Nicolas Bourriez, Thomas Boyer +3
Disentangled representation learning aims to map independent factors of variation to independent representation components. On one hand, purely unsupervised approaches have proven…
Deep Learning for BioImaging: What Are We Really Learning?
Ivan Svatko, Maxime Sanchez, Ihab Bendidi +2
Representation learning has driven major advances in natural image analysis by enabling models to acquire high-level semantic features. In microscopy imaging, however, it remains u…
Spectral Collapse in Diffusion Inversion
Nicolas Bourriez, Alexandre Verine, Auguste Genovesio
Conditional diffusion inversion provides a powerful framework for unpaired image-to-image translation. However, we demonstrate through an extensive analysis that standard determini…
Revealing Subtle Phenotypes in Small Microscopy Datasets Using Latent Diffusion Models
Anis Bourou, Biel Castaño Segade, Thomas Boyer +2
Identifying subtle phenotypic variations in cellular images is critical for advancing biological research and accelerating drug discovery. These variations are often masked by the…
Multi-marginal temporal Schrödinger Bridge Matching from unpaired data
Thomas Gravier, Thomas Boyer, Auguste Genovesio
Many natural dynamic processes -- such as in vivo cellular differentiation or disease progression -- can only be observed through the lens of static sample snapshots. While challen…