3 papers
q-bio.GN2026
A Standardized Framework For Evaluating Gene Expression Generative Models
Andrea Rubbi, Andrea Giuseppe Di Francesco, Mohammad Lotfollahi +1
The rapid development of generative models for single-cell gene expression data has created an urgent need for standardised evaluation frameworks. Current evaluation practices suff…
cs.LG2026
Retrieval-Augmented Generation for Predicting Cellular Responses to Gene Perturbation
Andrea Giuseppe Di Francesco, Andrea Rubbi, Pietro Liò
Predicting how cells respond to genetic perturbations is fundamental to understanding gene function, disease mechanisms, and therapeutic development. While recent deep learning app…
cs.LG2026
Shortest-Path Flow Matching with Mixture-Conditioned Bases for OOD Generalization to Unseen Conditions
Andrea Rubbi, Amir Akbarnejad, Mohammad Vali Sanian +10
Robust generalization under distribution shift remains a key challenge for conditional generative modeling: conditional flow-based methods often fit the training conditions well bu…