Reconstruction and stability in acousto-optic imaging for absorption maps with bounded variation

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It is well known and readily seen that the maximum of n independent and uniformly on [0, 1] distributed random variables, suitably standardised, converges in total variation distance, as n increases, to the standard negative exponential distribution. We ex ...

Given two probability measures P and Q and an event E, we provide bounds on P(E) in terms of Q(E) and f-divergences. In particular, the bounds are instantiated when the measures considered are a joint distribution and the corresponding product of marginals ...

Many scientific inquiries in natural sciences involve approximating a spherical field -namely a scalar quantity defined over a continuum of directions- from generalised samples of the latter (e.g. directional samples, local averages, etc). Such an approxim ...

Finite volume methods are proposed for computing approximate pathwise entropy/kinetic solutions to conservation laws with flux functions driven by low-regularity paths. For a convex flux, it is demonstrated that driving path oscillations may lead to "cance ...

This work proposes a method to measure the photon polarisation in

B^+ \rightarrow K^+ \pi^- \pi^+ \gamma

decays and prepares the necessary elements for this measurement using the data sets collected by the LHCb experiment at CERN in

2011

2012

, $2016 ...

Wasserstein distances are metrics on probability distributions inspired by the problem of optimal mass transportation. Roughly speaking, they measure the minimal effort required to reconfigure the probability mass of one distribution in order to recover th ...

Mathematical models involving multiple scales are essential for the description of physical systems. In particular, these models are important for the simulation of time-dependent phenomena, such as the heat flow, where the Laplacian contains mixed and ind ...

We propose a non-intrusive reduced basis (RB) method for parametrized nonlinear partial differential equations (PDEs) that leverages models of different accuracy. From a collection of low-fidelity (LF) snapshots, parameter locations are extracted for the e ...

Proper modeling of stochastic errors in inertial sensors plays a crucial role in the achievable quality of GNSS-INS integration especially with low-cost inertial sensors. Generalized Method of Wavelet Moments (GMWM) can model the underlying process for suc ...

Aggregate interlocking allows transferring shear and normal stresses through open cracks, and is considered to significantly contribute to the force transfer in cracked concrete. The complex phenomenon depends on the roughness of cracked surfaces, where ma ...

Probabilistic parameter estimation in model fitting runs the gamut from maximum likelihood or maximum a posteriori point estimates from optimization to Markov Chain Monte Carlo (MCMC) sampling. The latter, while more computationally intensive, generally pr ...

In this thesis, I aim to contribute to the research towards improving the sustainability of habitat life in streams affected by anthropogenic activities. With the growing trend of altering natural water regimes due to hydropower operations, irrigation, and ...

We consider Isogeometric Analysis (IGA) for the numerical solution of the electrophysiology of the atria, which in this work is modeled by means of the bidomain equations on thin surfaces. First, we consider the bidomain equations coupled with the Roger-Mc ...

Reconstruction and stability in acousto-optic imaging for absorption maps with bounded variation

Chattez avec Graph Search

Strong convergence of multivariate maxima

Robust Generalization via f−Mutual Information

Functional Inverse Problems on Spheres: Theory, Algorithms and Applications

Numerical methods for conservation laws with rough flux

Amplitude analysis for the measurement of the photon polarisation in B rightarrow K pi pi gamma decays

Statistical Aspects of Wasserstein Distances

Numerical methods for deterministic and stochastic differential equations with multiple scales and high contrasts

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Optimal Stochastic Sensor Error Modeling based on Actual Impact on Quality of GNSS-INS Integrated Navigation

Review of fundamental assumptions of the Two-Phase model for aggregate interlocking in cracked concrete using numerical methods and experimental evidence

Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler

Hydrological and hydraulic solutions for the sustainability of habitat life in human altered streams

Isogeometric Analysis of the electrophysiology in the human heart: Numerical simulation of the bidomain equations on the atria