Author

Giulio Franzese

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#machine learning Preprint Sep 2026

DRIFT: Disentangled Responsive-Invariant Flow Transport for Single-Cell Perturbation Prediction

Across several benchmarks, this method outperforms the strongest published method in settings involving combinatorial and unseen perturbation prediction, and is the strongest published method in settings involving combinatorial and unseen perturbation prediction.

Mustapha Bounoua, Giulio Franzese, Pietro Michiardi · 0 citations

#machine learning Preprint Sep 2026

ALICE: In-context, Zero-shot, Mutual Information Estimation

Estimating mutual information (MI) from samples is a central objective in a variety of scientific fields. Modern neural estimators are accurate in the large-data regime, but they fall short when data is scarce, and each must be fit anew for every distribution under study. Current estimators are moreover tied to specifi...

Giulio Franzese, Simone Rossi, Pietro Michiardi · 0 citations