Computational & statistical learning
Our aim is to advance the frontiers of learning theory and machine learning, while building algorithmic tools for the analysis of complex systems and high dimensional data.
Our aim is to advance the frontiers of learning theory and machine learning, while building algorithmic tools for the analysis of complex systems and high dimensional data.
Our scientific interests focus on harmonic analysis, inverse problems, PDE and machine learning.
We investigate different nuances of visual perception in artificial intelligence systems, where computer vision and machine learning are combined to obtain robust data-driven methods addressing a variety of problems.
We blend physics with machine learning and biological behavior to ask how organisms strive in a fluid environment dominated by uncertainty.
Ongoing grants
Ended grants
Research Fundings in the past 5yrs
Title | Year | Author | Venue |
---|---|---|---|
Introducing Temporal Correlation in Rainfall and Wind Prediction From Underwater Noise | 2023 | A Trucco A Barla R Bozzano S Pensieri A Verri David Solarna | IEEE JOURNAL OF OCEANIC ENGINEERING |
Kinematic primitives in action similarity judgments: A human-centered computational model | 2023 | V Nair P Hemeren A Vignolo N Noceti E Nicora A Sciutti F Rea E Billing M Bhatt F Odone G Sandini | IEEE Transactions on Cognitive and Developmental Systems |
Physics informed machine learning for wind speed prediction | 2023 | D Lagomarsino-Oneto G Meanti N Pagliana A Verri A Mazzino L Rosasco A Seminara | Energy, Volume 268, 2023, 126628 |
Iterative regularization in classification via hinge loss diagonal descent | 2023 | V Apidopoulos T Poggio L Rosasco S Villa | ArXiv Preprint |
The World of Graph Neural Networks: From the Mystery of Generalization to Foundational Limitations | 2022 | V Apidopoulos T Poggio L Rosasco S Villa | ArXiv Preprint |
Scalable Causal Discovery with Score Matching | 2022 | F Montagna N Noceti L Rosasco K Zhang F Locatello | NeurIPS 2022 Workshop on Score-Based Methods |
Implicit regularization with strongly convex bias: stability and acceleration | 2022 | S Villa S Matet BC Vũ L Rosasco | Analysis and Applications, 1-27, 2022 |
Learning new physics efficiently with nonparametric methods | 2022 | M Letizia G Losapio M Rando G Grosso A Wulzer M Pierini M Zanetti L Rosasco | The European Physical Journal C 82 (10), 879 |
Semantic Learning in a Federated Learning Sytem | 2022 | V Pastore Y Zhou N Baracaldo Angel A Anwar S Bianco | US Patent App. 17/818,132, 2022 |
Real time Vehicle Color Recognition on a budget: an investigation on the usage of CNN architectures | 2022 | S Campisi L Colombini A Lovato F Odone N Noceti | 2022 18th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2022, pp. 1-8 |