Luigi Bonati — accepted AI-conference papers

2026

Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems

Giacomo Turri, Luigi Bonati, Kai Zhu, Massimiliano Pontil, Pietro Novelli

ICLR 2026poster

We introduce an end-to-end approach to learn the evolution operators of large-scale non-linear dynamical systems, such as those describing complex natural phenomena. Evolution operators are particularly well-suited for analyzing systems that exhibit spatio-temporal patterns and have become a key ana…

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2023

Transfer learning for atomistic simulations using GNNs and kernel mean embeddings

John Isak Texas Falk, Luigi Bonati, Pietro Novelli, Michele Parrinello, Massimiliano Pontil

NeurIPS 2023poster

Interatomic potentials learned using machine learning methods have been successfully applied to atomistic simulations. However, accurate models require large training datasets, while generating reference calculations is computationally demanding. To bypass this difficulty, we propose a transfer lea…

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