Harmonic Analysis and Signal Processing
The research focus on frames that are defined in terms of square-integrable unitary representations of a locally compact group
The research focus on frames that are defined in terms of square-integrable unitary representations of a locally compact group
We are interested in inverse problems for elliptic and hyperbolic equations, including Calderon’s problem for electrical impedance tomography (EIT), photo-acoustic tomography (PAT), inverse scattering, Gel’fand-Calderon’s problem.
The activity is mainly devoted to show the interplay between learning theory and inverse problems.
Ángel Arroyo - Inverse problems
Salvatore Ivan Trapasso
Alessandro Ottazzi - Harmonic Analysis
Paolo Albini - Quantum Mechanics
Irene Venturi - Harmonic Analysis
Guido Cesare - Machine Learning
Lucia Mantovani - Harmonic Analysis
Francesca Bartolucci - Harmonic Analysis
Stefano Vigogna - Harmonic Analysis
Matteo Monti - Harmonic Analysis
Giuseppe Zampogna
Umberto De Giovannini - Machine Learning
Francesca Dotti - Machine Learning
Ilaria Giulini - Probability
Laura Gemme - Machine Learning
Manuela Barone - Signal Analysis
Elisa Businelli - Harmonic Analysis
Giulia Vignola - Signal Analysis
Arianna Romani - Harmonic Analysis
Anton Emelchenkov - Machine Learning for Inverse Problems
Nicola Raffo - Signal Analysis
Sandra Albani - Signal Analysis
Nicolò Pagliana - Machine Learning
Silvia Sciutto - Analysis & Measure Theory
Mattia Barisone - Signal Analysis
Eugenio Dellepiane - Analysis
Marco Baracchini - Analysis & Inverse Problems
Paolo Campodonico - Analysis & Inverse Problems
Davide Parodi - Machine Learning & Signal Analysis
Giulia Bollo - Machine Learning
Filippo Papallo - Analysis
Giuseppe Carta - Analysis
Silvia Sciutto - Signal Analysis
Lorenzo Bozzi - Analysis
Beatrice Ravera - Analysis
Geraldo Macoj - Machine Learning
Simone Sanna - Compressed Sensing
Luca Wellmeier
Camilla Casaleggi
Title | Principal Investigator | Funding | Start | End | Amount |
---|---|---|---|---|---|
Sample complexity for inverse problems in PDE | Giovanni S. Alberti - Principal Investigator | EU | ERC StG | 2022 | 2027 | 1.1500000000000001 M |
Compressed sensing for inverse problems in PDE | Giovanni S. Alberti - Principal Investigator | UniGe | 2021 | 2023 | 85k |
Machine Learning for Inverse Problems | Giovanni S. Alberti, Matteo Santacesaria - co-Principal Investigator | AFOSR - Air Force Office of Scientific Research | 2020 | 2023 | 220k |
Infinite-dimensional inverse problems with finite measurements | Giovanni S. Alberti - Principal Investigator | UniGe | UniGe Starting grant | 2019 | 2021 | 59k |
Applied harmonic analysis and PDEs for inverse problems in imaging | Giovanni S. Alberti - Principal Investigator | ETH Postdoctoral Fellowship: ETH Zurich & Marie-Curie actions | 2016 | 2018 | 215k |
Title | Year | Author | Venue |
---|---|---|---|
Manifold Learning by Mixture Models of VAEs for Inverse Problems | 2023 | GS Alberti J Hertrich M Santacesaria S Sciutto | ArXiv Preprint |
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 |
Optimal transport with nonlinear mobilities: a deterministic particle approximation result | 2022 | S Di Marino L Portinale E Radici | ArXiv Preprint |
Harmonic Bergman projectors and Calderón-Zygmund theory on homogeneous trees | 2022 | F De Mari M Monti M Vallarino | Research Gate |
Localized adversarial artifacts for compressed sensing MRI | 2022 | Alaifari R Alberti GS Gauksson T | ArXiv Preprint |