A Covariance Formula For Topological Events Of Smooth Gaussian Fields

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Euclid : Effects of sample covariance on the number counts of galaxy clusters

Aims. We investigate the contribution of shot-noise and sample variance to uncertainties in the cosmological parameter constraints inferred from cluster number counts, in the context of the Euclid survey. ...

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Network information theory studies the communication of information in a network and considers its fundamental limits. Motivating from the extensive presence of the networks in the daily life, the thesis studies the fundamental limits of particular network ...

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Deterministic error bounds for kernel-based learning techniques under bounded noise

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We consider the problem of reconstructing a function from a finite set of noise-corrupted samples. Two kernel algorithms are analyzed, namely kernel ridge regression and epsilon-support vector regression. By assuming the ground-truth function belongs to th ...

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Assessment of representativity of the PETALE experiments for validation of Swiss LWRs ex-core dosimetry calculations

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Certified And Fast Computations With Shallow Covariance Kernels

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Many techniques for data science and uncertainty quantification demand efficient tools to handle Gaussian random fields, which are defined in terms of their mean functions and covariance operators. Recently, parameterized Gaussian random fields have gained ...

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On the probability distribution of the local times of diagonally operator-self-similar Gaussian fields with stationary increments

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Maximum-Entropy Distributions offer an attractive family of probability densities suitable for moment closure problems. Yet finding the Lagrange multipliers which parametrize these distributions, turns out to be a computational bottleneck for practical clo ...

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