Fast homogenization algorithm based on asymptotic theory and multiscale schemes. - Maria Morandi Cecchi; Massimo Fornasier (Numer. Algorithms, 2005)

Fast, robust and efficient 2D pattern recognition for re-assembling fragmented images. - Massimo Fornasier; Domenico Toniolo (Pattern Recognit., 2005)

Nonlinear Projection Recovery in Digital Inpainting for Color Image Restoration. - Massimo Fornasier (J. Math. Imaging Vis., 2006)

Faithful Recovery of Vector Valued Functions from Incomplete Data. - Massimo Fornasier (SSVM, 2007)

Adaptive frame methods for elliptic operator equations. - Stephan Dahlke; Massimo Fornasier; Thorsten Raasch (Adv. Comput. Math., 2007)

Restoration of Color Images by Vector Valued BV Functions and Variational Calculus. - Massimo Fornasier; Riccardo March (SIAM J. Appl. Math., 2007)

Iteratively Re-weighted Least Squares minimization: Proof of faster than linear rate for sparse recovery. - Ingrid Daubechies; Ronald A. DeVore; Massimo Fornasier; C. Sinan Güntürk (CISS, 2008)

Adaptive frame methods for nonlinear variational problems. - Maria Charina; Costanza Conti; Massimo Fornasier (Numerische Mathematik, 2008)

Recovery Algorithms for Vector-Valued Data with Joint Sparsity Constraints. - Massimo Fornasier; Holger Rauhut (SIAM J. Numer. Anal., 2008)

Compressive Algorithms-Adaptive Solutions of PDEs and Variational Problems. - Massimo Fornasier (IMA Conference on the Mathematics of Surfaces, 2009)

The application of joint sparsity and total variation minimization algorithms to a real-life art restoration problem. - Massimo Fornasier; Ronny Ramlau; Gerd Teschke (Adv. Comput. Math., 2009)

Subspace Correction Methods for Total Variation and 1-Minimization. - Massimo Fornasier; Carola-Bibiane Schönlieb (SIAM J. Numer. Anal., 2009)

Theoretical Foundations and Numerical Methods for Sparse Recovery. - Massimo Fornasier (de Gruyter, 2010)

Iterative Thresholding Meets Free-Discontinuity Problems. - Massimo Fornasier; Rachel A. Ward (Found. Comput. Math., 2010)

Optimal adaptive computations in the Jaffard algebra and localized frames. - Stephan Dahlke; Massimo Fornasier; Karlheinz Gröchenig (J. Approx. Theory, 2010)

A convergent overlapping domain decomposition method for total variation minimization. - Massimo Fornasier; Andreas Langer; Carola-Bibiane Schönlieb (Numerische Mathematik, 2010)

Asymptotic Flocking Dynamics for the Kinetic Cucker-Smale Model. - José A. Carrillo 001; Massimo Fornasier; Jesús Rosado; Giuseppe Toscani (SIAM J. Math. Anal., 2010)

Particle Systems and Kinetic Equations Modeling Interacting Agents in High Dimension. - Massimo Fornasier; Jan Haskovec; Jan Vybíral (Multiscale Model. Simul., 2011)

Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization. - Massimo Fornasier; Holger Rauhut; Rachel A. Ward (SIAM J. Optim., 2011)

Learning Functions of Few Arbitrary Linear Parameters in High Dimensions. - Massimo Fornasier; Karin Schnass; Jan Vybíral (Found. Comput. Math., 2012)

Multilevel preconditioning and adaptive sparse solution of inverse problems. - Stephan Dahlke; Massimo Fornasier; Thorsten Raasch (Math. Comput., 2012)

Wavelet Decomposition Method for L2//TV-Image Deblurring. - Massimo Fornasier; Yunho Kim; Andreas Langer; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2012)

Anisotropic Adaptive Meshes for Brittle Fractures: Parameter Sensitivity. - Marco Artina; Massimo Fornasier; Stefano Micheletti; Simona Perotto (ENUMATH, 2013)

Linearly Constrained Nonsmooth and Nonconvex Minimization. - Marco Artina; Massimo Fornasier; Francesco Solombrino (SIAM J. Optim., 2013)

Mean-field optimal control by leaders. - Massimo Fornasier; Benedetto Piccoli; Nastassia Pouradier Duteil; Francesco Rossi (CDC, 2014)

Sparse control of force field dynamics. - Mattia Bongini; Massimo Fornasier; Fabian Frcohlich; Laleh Haghverdi (NetGCooP, 2014)

Quasi-linear Compressed Sensing. - Martin Ehler; Massimo Fornasier; Juliane Sigl (Multiscale Model. Simul., 2014)

Sparse stabilization of dynamical systems driven by attraction and avoidance forces. - Mattia Bongini; Massimo Fornasier (Networks Heterog. Media, 2014)

Asymptotic Behavior of Gradient Flows Driven by Nonlocal Power Repulsion and Attraction Potentials in One Dimension. - Marco Di Francesco; Massimo Fornasier; Jan-Christian Hütter; Daniel Matthes (SIAM J. Math. Anal., 2014)

Parameter Choice Strategies for Multipenalty Regularization. - Massimo Fornasier; Valeriya Naumova; Sergei V. Pereverzyev (SIAM J. Numer. Anal., 2014)

Sparse control of alignment models in high dimension. - Mattia Bongini; Massimo Fornasier; Oliver Junge; Benjamin Scharf (Networks Heterog. Media, 2015)

Anisotropic Mesh Adaptation for Crack Detection In Brittle Materials. - Marco Artina; Massimo Fornasier; Stefano Micheletti; Simona Perotto (SIAM J. Sci. Comput., 2015)

Damping Noise-Folding and Enhanced Support Recovery in Compressed Sensing. - Steffen Peter; Marco Artina; Massimo Fornasier (IEEE Trans. Signal Process., 2015)

Compressive Sensing. - Massimo Fornasier; Holger Rauhut (Handbook of Mathematical Methods in Imaging, 2015)

Conjugate gradient acceleration of iteratively re-weighted least squares methods. - Massimo Fornasier; Steffen Peter; Holger Rauhut; Stephan Worm (Comput. Optim. Appl., 2016)

Mean-Field Pontryagin Maximum Principle. - Mattia Bongini; Massimo Fornasier; Francesco Rossi; Francesco Solombrino (J. Optim. Theory Appl., 2017)

Identification of Shallow Neural Networks by Fewest Samples. - Massimo Fornasier; Jan Vybíral; Ingrid Daubechies (CoRR, 2018)

Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks. - Massimo Fornasier; Timo Klock; Michael Rauchensteiner (CoRR, 2019)

Data-driven Evolutions of Critical Points. - Stefano Almi; Massimo Fornasier; Richard Huber (CoRR, 2019)

Consensus-based Optimization on the Sphere II: Convergence to Global Minimizers and Machine Learning. - Massimo Fornasier; Hui Huang; Lorenzo Pareschi; Philippe Sünnen (CoRR, 2020)

Consensus-Based Optimization on the Sphere I: Well-Posedness and Mean-Field Limit. - Massimo Fornasier; Hui Huang; Lorenzo Pareschi; Philippe Sünnen (CoRR, 2020)

A Relaxed Kačanov iteration for the p-poisson problem. - Lars Diening; Massimo Fornasier; Roland Tomasi; Maximilian Wank (Numerische Mathematik, 2020)

Robust recovery of low-rank matrices with non-orthogonal sparse decomposition from incomplete measurements. - Massimo Fornasier; Johannes Maly; Valeriya Naumova (Appl. Math. Comput., 2021)

Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples. - Christian Fiedler; Massimo Fornasier; Timo Klock; Michael Rauchensteiner (CoRR, 2021)

Consensus-based optimization methods converge globally in mean-field law. - Massimo Fornasier; Timo Klock; Konstantin Riedl (CoRR, 2021)

Consensus-Based Optimization on the Sphere: Convergence to Global Minimizers and Machine Learning. - Massimo Fornasier; Lorenzo Pareschi; Hui Huang; Philippe Sünnen (J. Mach. Learn. Res., 2021)

Convergence of Anisotropic Consensus-Based Optimization in Mean-Field Law. - Massimo Fornasier; Timo Klock; Konstantin Riedl (EvoApplications, 2022)

Finite Sample Identification of Wide Shallow Neural Networks with Biases. - Massimo Fornasier; Timo Klock; Marco Mondelli; Michael Rauchensteiner (CoRR, 2022)

Anisotropic Diffusion in Consensus-Based Optimization on the Sphere. - Massimo Fornasier; Hui Huang; Lorenzo Pareschi; Philippe Sünnen (SIAM J. Optim., 2022)

Gradient is All You Need? - Konstantin Riedl; Timo Klock; Carina Geldhauser; Massimo Fornasier (CoRR, 2023)

From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks. - Cristina Cipriani; Massimo Fornasier; Alessandro Scagliotti (CoRR, 2023)

Approximation Theory, Computing, and Deep Learning on the Wasserstein Space. - Massimo Fornasier; Pascal Heid; Giacomo Enrico Sodini (CoRR, 2023)

Solving partial differential equations with sampled neural networks. - Chinmay Datar; Taniya Kapoor; Abhishek Chandra; Qing Sun; Iryna Burak; Erik Lien Bolager; Anna Veselovska; Massimo Fornasier; Felix Dietrich (CoRR, 2024)

Consensus-Based Optimization Methods Converge Globally. - Massimo Fornasier; Timo Klock; Konstantin Riedl (SIAM J. Optim., 2024)