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 |
Be greedy and learn: efficient and certified algorithms for parametrized optimal control problems | 2023 | H Kleikamp M Lazar C Molinari | ArXiv Preprint |
An efficient deep learning approach to identify dynamics in in vitro neural networks | 2023 | VP Pastore G Parodi M Brofiga P Massobrio M Chiappalone F Odone S Martinoia | Arinex, EMBC |
The five gradients inequality on differentiable manifolds | 2023 | S Di Marino S Murro E Radici | ArXiv Preprint |
Efficient unsupervised learning of biological images with compressed deep features | 2023 | VP Pastore M Ciranni S Bianco JC Fung V Murino F Odone | Image and Vision Computing, Volume 137 |
Variance reduction techniques for stochastic proximal point algorithms | 2023 | C Traoré V Apidopoulos S Salzo S Villa | ArXiv Preprint |
An Automatic Tool Performing Functional Analysis in MR Urography in Children | 2023 | E Vincenzi A Fantazzini M Gulino S Manini A Verri F Odone L Basso M B Damasio C Basso | 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), L'Aquila, Italy, 2023, pp. 845-851 |
In-domain versus out-of-domain transfer learning in plankton image classification | 2023 | A Maracani VP Pastore L Natale L Rosasco F Odone | Scientific Reports, 2023 |
Estimating Koopman operators with sketching to provably learn large scale dynamical systems | 2023 | G Meanti A Chatalic V Kostic P Novelli M Pontil L Rosasco | ArXiv Preprint |
A Grasp Pose is All You Need: Learning Multi-fingered Grasping with Deep Reinforcement Learning from Vision and Touch | 2023 | F Ceola E Maiettini L Rosasco L Natale | ArXiv Preprint |