Publications related to Inverse Analysis of Radiative Flux Maps for the Characterization of High Flux Sources

Robust and adaptive approaches for Relative Geologic Time Estimation

For a geoscientist, the Relative Geologic Time (RGT) is an important tool to perform chronostratigraphic analysis. However, automatically estimate an RGT image from a seismic image can be a challenging task where we have to respect seismic features, the de ...

ELSEVIER SCIENCE BV2018

Deriving fragility functions from bilinearized capacity curves for earthquake scenario modelling using the conditional spectrum

Pierino Lestuzzi, Clotaire Michel, Pia Hannewald

The development of fragility curves to perform seismic scenario-based risk assessment requires a fully probabilistic procedure in order to account for uncertainties at each step of the computation. This is especially true when developing fragility curves c ...

SPRINGER2018

The regularized tau estimator: A robust and efficient solution to ill-posed linear inverse problems

Martin Vetterli, Benjamin Bejar Haro, Marta Martinez-Camara

Linear inverse problems are ubiquitous. Often the measurements do not follow a Gaussian distribution. Additionally, a model matrix with a large condition number can complicate the problem further by making it ill-posed. In this case, the performance of pop ...

2017

Assessment of the Probability of Collapse of Structures Under Earthquakes

Dimitrios Lignos

Avoidance of collapse is the most important objective in earthquake resistant design, but assessing the probability of collapse of a structure during an earthquake is technically challenging and it is computationally demanding. This paper summarizes recent ...

International Association of Earthquake Engineering2017

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

Emrah Bostan

We propose new regularization models to solve inverse problems encountered in biomedical imaging applications. In formulating mathematical schemes, we base our approach on the sparse signal processing principles that have emerged as a central paradigm in t ...

EPFL2016

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Michaël Unser, Julien René Pierre Fageot, Harshit Gupta

We present a theoretical analysis and comparison of the effect of

ℓ _{ 1 }

versus

ℓ _{ 2 }

regularization for the resolution of ill-posed linear inverse and/or compressed sensing problems. Our formulation covers the most general setting where the s ...

IEEE2016

Sparse regularization methods in ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Adrien Georges Jean Besson, Olivier Bernard

Ultrafast ultrasound (US) imaging based on plane wave (PW) insonification is a widely used modality nowadays. Two main types of approaches have been proposed for image reconstruction either based on classical delay-and-sum (DAS) or on Fourier reconstructio ...

Ieee2016

PURIFY: a new approach to radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

In a recent article series, the authors have promoted convex optimization algorithms for radio-interferometric imaging in the framework of compressed sensing, which leverages sparsity regularization priors for the associated inverse problem and defines a m ...

Wiley-Blackwell2014

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$

Jean-Philippe Thiran, Dimitri Nestor Alice Van De Ville, Yves Wiaux, Alessandro Daducci

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. F ...

Institute of Electrical and Electronics Engineers2014

Stability and Hypothesis Transfer Learning

Ilja Kuzborskij

We consider the transfer learning scenario, where the learner does not have access to the source domain directly, but rather operates on the basis of hypotheses induced from it - the Hypothesis Transfer Learning (HTL) problem. Particularly, we conduct a th ...

2013

Inverse Analysis of Radiative Flux Maps for the Characterization of High Flux Sources

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Robust and adaptive approaches for Relative Geologic Time Estimation

Deriving fragility functions from bilinearized capacity curves for earthquake scenario modelling using the conditional spectrum

The regularized tau estimator: A robust and efficient solution to ill-posed linear inverse problems

Assessment of the Probability of Collapse of Structures Under Earthquakes

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Sparse regularization methods in ultrafast ultrasound imaging

PURIFY: a new approach to radio-interferometric imaging

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$

Stability and Hypothesis Transfer Learning

The regularized tau estimator: A robust and efficient solution to ill-posed linear inverse problems

Sparse regularization methods in ultrafast ultrasound imaging

Robust and adaptive approaches for Relative Geologic Time Estimation

Deriving fragility functions from bilinearized capacity curves for earthquake scenario modelling using the conditional spectrum

PURIFY: a new approach to radio-interferometric imaging

Stability and Hypothesis Transfer Learning

Assessment of the Probability of Collapse of Structures Under Earthquakes

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$