Compressive sensing meets game theory

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Compressive sensing meets game theory

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Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Neural ADMIXTURE for rapid genomic clustering

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

Mesh d-refinement: a data-based computational framework to account for complex material response

A Least-Squares Method for the Solution of the Non-smooth Prescribed Jacobian Equation

A Structured Dictionary Perspective on Implicit Neural Representations

Rapid Scalable Distributed Power Flow with Open-Source Implementation

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

From Undercomplete to Sparse Overcomplete Autoencoders to Improve LF-MMI Speech Recognition

Comparison of non-parametric T2 relaxometry methods for myelin water quantification

Multikernel Regression with Sparsity Constraint

Continuous-Domain Formulation of Inverse Problems for Composite Sparse-Plus-Smooth Signals

Dictionary Learning for Two-Dimensional Kendall Shapes

Development and evaluation of galaxy shape measurement algorithms for radio interferometric data

Convex optimization in sums of Banach spaces

Functional lagged regression with sparse noisy observations

Dynamic Model Pruning with Feedback