Author

Davide D'Ascenzo

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Open access Nov 2026

Single-cell perturbation prediction near experimental reproducibility with GENESIS

Single-cell perturbation atlases now measure cellular responses across millions of cells, but the number of possible combinations of biological contexts, perturbations, doses and other experimental variables make exhaustive measurements infeasible. Here, we present GENESIS (Generative ENErgy-based Single-cell Intervent...

Riccardo Conci, Davide D'Ascenzo, Sebastiano Cultrera di Montesano et al. · bioRxiv · 0 citations

Preprint Oct 2026

LocaLeJEPA: Maximum Entropy Representations under Geometric Priors

Joint-Embedding Predictive Architectures (JEPA) offer an appealing approach to self-supervised learning, but are typically prone to representation collapse. LeJEPA resolves this by introducing a theoretically grounded distribution-matching objective that drives the embedding towards an isotropic Gaussian. However, this...

Kartik Tandon, Alessio Borgi, Pavel Snopov et al. · 0 citations