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The objective of the present study was to develop a model to predict lichen species richness for six test sites in the Swiss Pre-Alps following a gradient of land use intensity combining airborne re...
Our goal in this paper is to examine the discovery potential of laboratory experiments searching for the oscillation lk(le)Plq, in the light of recent data on solar and atmospheric neutrino experiment...
In this thesis we present new results for the 99.9% confidence level flux upper limits on the pulsed VHE gamma ray signal coming from the Crab pulsar. In order to achieve optimum hadronic background s...
A kernel based procedure for correcting experimental data for distortions due to the finite resolution and limited detector acceptance is presented. The unfolding problem is known to be an ill-posed p...
This work is concerned with a direct sampling method (DSM) for inverse acoustic scattering problems using far-field data. The method characterizes some unknown obstacles, inhomogeneous media or cracks...
The implicit particle filter is a sequential Monte Carlo method for data assimilation that guides the particles to the high-probability regions via a sequence of steps that includes minimizations. We ...
Abstract: Data gaps are ubiquitous in spectral irradiance data, and yet, little effort has been put into finding robust methods for filling them. We introduce a data-adaptive and nonparametric method ...
Abstract: We show that a method based on logistic regression, using all the data, solves the inverse Ising problem far better than mean-field calculations relying only on sample pairwise correlation f...
Abstract: We derive a method to reconstruct Gaussian signals from linear measurements with Gaussian noise. This new algorithm is intended for applications in astrophysics and other sciences. The start...
Abstract: This paper presents the application of a particle filter for data assimilation in the context of puff-based dispersion models. Particle filters provide estimates of the higher moments, and a...
Abstract: Tomograms, a generalization of the Radon transform to arbitrary pairs of non-commuting operators, are positive bilinear transforms with a rigorous probabilistic interpretation which provide ...
Abstract: We develop a scheme for estimating state-dependent drift and diffusion coefficients in a stochastic differential equation from a time-series data. There is no need to have any prior knowledg...
Abstract: Data assimilation refers to methodologies for the incorporation of noisy observations of a physical system into an underlying model in order to infer the properties of the state of the syste...
The present article considers time symmetric initial data sets for the vacuum Einstein field equations which in a neighbourhood of infinity have the same massless part as that of some static initial d...
In the light pseudoscalar sector, we study rooted staggered chiral perturbation theory in the two-flavor case. The pion mass and decay constant are calculated through NLO for a partiallyquenched theo...

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