Alexis Goujon

Orcid: 0000-0002-2198-0365

According to our database1, Alexis Goujon authored at least 12 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
On the number of regions of piecewise linear neural networks.
J. Comput. Appl. Math., May, 2024

Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms.
SIAM J. Imaging Sci., March, 2024

Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions.
J. Mach. Learn. Res., 2024

Controlled Learning of Pointwise Nonlinearities in Neural-Network-Like Architectures.
CoRR, 2024

2023
Approximation of Lipschitz Functions Using Deep Spline Neural Networks.
SIAM J. Math. Data Sci., June, 2023

A Neural-Network-Based Convex Regularizer for Inverse Problems.
IEEE Trans. Computational Imaging, 2023

2022
A Neural-Network-Based Convex Regularizer for Image Reconstruction.
CoRR, 2022

Delaunay-Triangulation-Based Learning with Hessian Total-Variation Regularization.
CoRR, 2022

The Role of Depth, Width, and Activation Complexity in the Number of Linear Regions of Neural Networks.
CoRR, 2022

Stable Parametrization of Continuous and Piecewise-Linear Functions.
CoRR, 2022

2021
Shortest-support multi-spline bases for generalized sampling.
J. Comput. Appl. Math., 2021

2020
Shortest Multi-Spline Bases for Generalized Sampling.
CoRR, 2020


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