Pietro Novelli

According to our database, Pietro Novelli authored at least 14 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Neural Conditional Probability for Inference.

Vladimir R. Kostic, Karim Lounici, Grégoire Pacreau, Pietro Novelli, Giacomo Turri, Massimiliano Pontil

CoRR, 2024

Operator World Models for Reinforcement Learning.

Pietro Novelli, Marco Pratticò, Massimiliano Pontil, Carlo Ciliberto

CoRR, 2024

Dynamics harmonic analysis of robotic systems: Application in data-driven Koopman modelling.

Daniel Felipe Ordoñez Apraez, Vladimir Kostic, Giulio Turrisi, Pietro Novelli, Carlos Mastalli, Claudio Semini, Massimiliano Pontil

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Consistent Long-Term Forecasting of Ergodic Dynamical Systems.

Vladimir R. Kostic, Karim Lounici, Prune Inzerilli, Pietro Novelli, Massimiliano Pontil

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning invariant representations of time-homogeneous stochastic dynamical systems.

Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

A randomized algorithm to solve reduced rank operator regression.

Giacomo Turri, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil

CoRR, 2023

Deep projection networks for learning time-homogeneous dynamical systems.

Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil

CoRR, 2023

Koopman Operator Learning: Sharp Spectral Rates and Spurious Eigenvalues.

Vladimir Kostic, Karim Lounici, Pietro Novelli, Massimiliano Pontil

CoRR, 2023

Estimating Koopman operators with sketching to provably learn large scale dynamical systems.

Giacomo Meanti, Antoine Chatalic, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sharp Spectral Rates for Koopman Operator Learning.

Vladimir Kostic, Karim Lounici, Pietro Novelli, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Transfer learning for atomistic simulations using GNNs and kernel mean embeddings.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Learning dynamical systems: an example from open quantum system dynamics.

Pietro Novelli

CoRR, 2022

Characterizing metastable states with the help of machine learning.

Pietro Novelli, Luigi Bonati, Massimiliano Pontil, Michele Parrinello

CoRR, 2022

Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces.

Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022