Infinite dimensional compressed sensing from anisotropic measurements. - Giovanni S. Alberti; Matteo Santacesaria (CoRR, 2017)

Reconstruction of a piecewise constant conductivity on a polygonal partition via shape optimization in EIT. - Elena Beretta; Stefano Micheletti; Simona Perotto; Matteo Santacesaria (J. Comput. Phys., 2018)

On an inverse Robin spectral problem. - Matteo Santacesaria; Toshiaki Yachimura (CoRR, 2019)

Neural networks for classification of strokes in electrical impedance tomography on a 3D head model. - Valentina Candiani; Matteo Santacesaria (CoRR, 2020)

Learning the optimal Tikhonov regularizer for inverse problems. - Giovanni S. Alberti; Ernesto De Vito; Matti Lassas; Luca Ratti; Matteo Santacesaria (NeurIPS, 2021)

Learning the optimal regularizer for inverse problems. - Giovanni S. Alberti; Ernesto De Vito; Matti Lassas; Luca Ratti; Matteo Santacesaria (CoRR, 2021)

Compressed Sensing Photoacoustic Tomography Reduces to Compressed Sensing for Undersampled Fourier Measurements. - Giovanni S. Alberti; Paolo Campodonico; Matteo Santacesaria (SIAM J. Imaging Sci., 2021)

Continuous Generative Neural Networks. - Giovanni S. Alberti; Matteo Santacesaria; Silvia Sciutto (CoRR, 2022)

Compressed sensing for inverse problems and the sample complexity of the sparse Radon transform. - Giovanni S. Alberti; Alessandro Felisi; Matteo Santacesaria; S. Ivan Trapasso (CoRR, 2023)

Market areas in general equilibrium. - Gianandrea Lanzara; Matteo Santacesaria (J. Econ. Theory, 2023)

Is In-Domain Data Beneficial in Transfer Learning for Landmarks Detection in X-Ray Images? - Roberto Di Via; Matteo Santacesaria; Francesca Odone; Vito Paolo Pastore (ISBI, 2024)

Learning a Gaussian Mixture for Sparsity Regularization in Inverse Problems. - Giovanni S. Alberti; Luca Ratti; Matteo Santacesaria; Silvia Sciutto (CoRR, 2024)

Learning sparsity-promoting regularizers for linear inverse problems. - Giovanni S. Alberti; Ernesto De Vito; Tapio Helin; Matti Lassas; Luca Ratti; Matteo Santacesaria (CoRR, 2024)

Manifold Learning by Mixture Models of VAEs for Inverse Problems. - Giovanni S. Alberti; Johannes Hertrich; Matteo Santacesaria; Silvia Sciutto (J. Mach. Learn. Res., 2024)

Localization of Point Scatterers via Sparse Optimization on Measures. - Giovanni S. Alberti; Romain Petit; Matteo Santacesaria (SIAM J. Imaging Sci., 2024)

Guest Editorial JMIV Special Issue SSVM'23. - Luca Calatroni; Marco Donatelli; Serena Morigi; Marco Prato; Matteo Santacesaria (J. Math. Imaging Vis., 2024)

Assessing the Use of Diffusion Models for Motion Artifact Correction in Brain MRI. - Paolo Angella; Vito Paolo Pastore; Matteo Santacesaria (ISBI, 2025)

TomoSelfDEQ: Self-supervised Deep Equilibrium Learning for Sparse-Angle CT Reconstruction. - Tatiana A. Bubba; Matteo Santacesaria; Andrea Sebastiani (SSVM (1), 2025)

Compressed sensing for inverse problems II: applications to deconvolution, source recovery, and MRI. - Giovanni S. Alberti; Alessandro Felisi; Matteo Santacesaria; S. Ivan Trapasso (CoRR, 2025)

DIMA: DIffusing Motion Artifacts for unsupervised correction in brain MRI images. - Paolo Angella; Luca Balbi; Fabrizio Ferrando; Paolo Traverso; Rosario Varriale; Vito Paolo Pastore; Matteo Santacesaria (CoRR, 2025)

Deep Unfolding Network for Nonlinear Multi-Frequency Electrical Impedance Tomography. - Giovanni S. Alberti; Damiana Lazzaro; Serena Morigi; Luca Ratti; Matteo Santacesaria (CoRR, 2025)