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Spatial and temporal regularization to estimate COVID-19 reproduction number R(t): Promoting piecewise smoothness via convex optimization
Among the different indicators that quantify the spread of an epidemic such as the on-going
COVID-19, stands first the reproduction number which measures how many people can be …
COVID-19, stands first the reproduction number which measures how many people can be …
A deep primal-dual proximal network for image restoration
Image restoration remains a challenging task in image processing. Numerous methods
tackle this problem, which is often solved by minimizing a nonsmooth penalized co-log …
tackle this problem, which is often solved by minimizing a nonsmooth penalized co-log …
Nonsmooth convex optimization to estimate the Covid-19 reproduction number space-time evolution with robustness against low quality data
Daily pandemic surveillance, often achieved through the estimation of the reproduction
number, constitutes a critical challenge for national health authorities to design counter …
number, constitutes a critical challenge for national health authorities to design counter …
A variational approach for joint image recovery and feature extraction based on spatially varying generalised Gaussian models
The joint problem of reconstruction/feature extraction is a challenging task in image
processing. It consists in performing, in a joint manner, the restoration of an image and the …
processing. It consists in performing, in a joint manner, the restoration of an image and the …
Risk Estimate under a Nonstationary Autoregressive Model for Data-Driven Reproduction Number Estimation
COVID-19 pandemic has brought to the fore epidemiological models which, though
describing a rich variety of behaviors, have previously received little attention in the signal …
describing a rich variety of behaviors, have previously received little attention in the signal …
Parameter-free and fast nonlinear piecewise filtering: application to experimental physics
Numerous fields of nonlinear physics, very different in nature, produce signals and images
that share the common feature of being essentially constituted of piecewise homogeneous …
that share the common feature of being essentially constituted of piecewise homogeneous …
Hyperparameter selection for discrete Mumford–Shah
This work focuses on a parameter-free joint piecewise smooth image denoising and contour
detection. Formulated as the minimization of a discrete Mumford–Shah functional and …
detection. Formulated as the minimization of a discrete Mumford–Shah functional and …
Restart strategies enabling automatic differentiation for hyperparameter tuning in inverse problems
Numerous signal/image processing tasks can be formulated as variational problems, whose
solutions depend, often crucially, on the values of hyperparameters. Their automated …
solutions depend, often crucially, on the values of hyperparameters. Their automated …
Spectral Total-variation Processing of Shapes—Theory and Applications
We present a comprehensive analysis of total variation (TV) on non-Euclidean domains and
its eigenfunctions. We specifically address parameterized surfaces, a natural representation …
its eigenfunctions. We specifically address parameterized surfaces, a natural representation …
Contributions to stochastic bilevel optimization
M Dagreou - 2024 - theses.hal.science
Bilevel problems are a type of optimization problem characterized by a hierarchical
structure. In these problems, one wants to minimize an outer function under the constraint …
structure. In these problems, one wants to minimize an outer function under the constraint …