Person
Alexis Marie Frederic Goujon
Related publications (8)
On the number of regions of piecewise linear neural networks
Michaël Unser, Alexis Marie Frederic Goujon
Many feedforward neural networks (NNs) generate continuous and piecewise-linear (CPWL) mappings. Specifically, they partition the input domain into regions on which the mapping is affine. The number of these so-called linear regions offers a natural metric ...
2024Towards Trustworthy Deep Learning for Image Reconstruction
The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...
EPFL2024A Neural-Network-Based Convex Regularizer for Inverse Problems
Michaël Unser, Pakshal Narendra Bohra, Alexis Marie Frederic Goujon, Sebastian Jonas Neumayer, Stanislas Ducotterd
The emergence of deep-learning-based methods to solve image-reconstruction problems has enabled a significant increase in quality. Unfortunately, these new methods often lack reliability and explainability, and there is a growing interest to address these ...
2023Stable parameterization of continuous and piecewise-linear functions
Michaël Unser, Alexis Marie Frederic Goujon, Joaquim Gonçalves Garcia Barreto Campos
Rectified-linear-unit (ReLU) neural networks, which play a prominent role in deep learning, generate continuous and piecewise-linear (CPWL) functions. While they provide a powerful parametric representation, the mapping between the parameter and function s ...
2023Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"
Michaël Unser, Pakshal Narendra Bohra, Alexis Marie Frederic Goujon, Sebastian Jonas Neumayer, Stanislas Ducotterd
Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...
EPFL Infoscience2023Emergent order in hydrodynamic spin lattices
Alexis Marie Frederic Goujon, John Bush
Macroscale analogues(1-3) of microscopic spin systems offer direct insights into fundamental physical principles, thereby advancing our understanding of synchronization phenomena(4) and informing the design of novel classes of chiral metamaterials(5-7). He ...
NATURE PORTFOLIO2021Shortest-support multi-spline bases for generalized sampling
Michaël Unser, Alexis Marie Frederic Goujon, Shayan Aziznejad, Alireza Naderi
Generalized sampling consists in the recovery of a function f, from the samples of the responses of a collection of linear shift-invariant systems to the input f . The reconstructed function is typically a member of a finitely generated integer-shift invar ...
2021