Shortest Multi-Spline Bases for Generalized Sampling. - Alexis Goujon; Shayan Aziznejad; Alireza Naderi; Michael Unser (CoRR, 2020)

Shortest-support multi-spline bases for generalized sampling. - Alexis Goujon; Shayan Aziznejad; Alireza Naderi; Michael Unser (J. Comput. Appl. Math., 2021)

Stable Parametrization of Continuous and Piecewise-Linear Functions. - Alexis Goujon; Joaquim Campos; Michael Unser (CoRR, 2022)

The Role of Depth, Width, and Activation Complexity in the Number of Linear Regions of Neural Networks. - Alexis Goujon; Arian Etemadi; Michael Unser (CoRR, 2022)

Delaunay-Triangulation-Based Learning with Hessian Total-Variation Regularization. - Mehrsa Pourya; Alexis Goujon; Michael Unser (CoRR, 2022)

A Neural-Network-Based Convex Regularizer for Image Reconstruction. - Alexis Goujon; Sebastian Neumayer; Pakshal Bohra; Stanislas Ducotterd; Michael Unser (CoRR, 2022)

A Neural-Network-Based Convex Regularizer for Inverse Problems. - Alexis Goujon; Sebastian Neumayer; Pakshal Bohra; Stanislas Ducotterd; Michael Unser (IEEE Trans. Computational Imaging, 2023)

Approximation of Lipschitz Functions Using Deep Spline Neural Networks. - Sebastian Neumayer; Alexis Goujon; Pakshal Bohra; Michael Unser (SIAM J. Math. Data Sci., 2023)

Controlled Learning of Pointwise Nonlinearities in Neural-Network-Like Architectures. - Michael Unser; Alexis Goujon; Stanislas Ducotterd (CoRR, 2024)

Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions. - Stanislas Ducotterd; Alexis Goujon; Pakshal Bohra; Dimitris Perdios; Sebastian Neumayer; Michael Unser (J. Mach. Learn. Res., 2024)

Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms. - Alexis Goujon; Sebastian Neumayer; Michael Unser (SIAM J. Imaging Sci., 2024)

On the number of regions of piecewise linear neural networks. - Alexis Goujon; Arian Etemadi; Michael Unser (J. Comput. Appl. Math., 2024)