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 |
Automatic Video Analysis and Classification of Sleep‐related Hypermotor seizures and Disorders of Arousal | 2023 | M Moro V P Pastore G Marchesi P Proserpio L Tassi A Castelnovo M Manconi G Nobile R Cordani S A. Gibbs F Odone M Casadio , et al. | Epilepsia |
Manifold Learning by Mixture Models of VAEs for Inverse Problems | 2023 | GS Alberti J Hertrich M Santacesaria S Sciutto | ArXiv Preprint |
Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test | 2023 | G Grosso N Lai M Letizia J Pazzini M Rando L Rosasco A Wulzer M Zanetti | ArXiv Preprint |
Universal diagonal estimates for minimizers of the Levy-Lieb functional | 2023 | S. Di Marino A. Gerolin L. Nenna | ArXiv Preprint |
Differences in spore size and atmospheric survival shape stark contrasts in the dispersal dynamics of two closely related fungal pathogens | 2023 | J Golan D Lagomarsino Oneto S Ding R Kessenich M Sandler T A. Rush D Levitis A Gevens A Seminara A Pringle | BioRxiv |
Compressed sensing for inverse problems and the sample complexity of the sparse Radon transform | 2023 | GS Alberti A Felisi M Santacesaria SI Trapasso | ArXiv Preprint |
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 |
Uncertainty-aware Gaze Tracking for Assisted Living Environments | 2023 | P Her L Manderle P A Dias H Medeiros F Odone | IEEE Transactions on Image Processing |
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 |