6 papers · 1 filter
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…
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…
DiViD: Disentangled Video Diffusion for Static-Dynamic Factorization
Marzieh Gheisari, Auguste Genovesio
Unsupervised disentanglement of static appearance and dynamic motion in video remains a fundamental challenge, often hindered by information leakage and blurry reconstructions in e…
DiffEx: Explaining a Classifier with Diffusion Models to Identify Microscopic Cellular Variations
Anis Bourou, Saranga Kingkor Mahanta, Thomas Boyer +2
In recent years, deep learning models have been extensively applied to biological data across various modalities. Discriminative deep learning models have excelled at classifying i…