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Choquet random sup-measures with aggregations
A variation of Choquet random sup-measures is introduced. These random sup-measures are shown to arise as the scaling limits of empirical random...
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Dynamical Large Deviations for an Inhomogeneous Wave Kinetic Theory: Linear Wave Scattering by a Random Medium
The wave kinetic equation predicts the averaged temporal evolution of a continuous spectral density of waves either randomly interacting or scattered...
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Random World and Quantum Mechanics
Quantum mechanics (QM) predicts probabilities on the fundamental level which are, via Born probability law, connected to the formal randomness of...
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Implicit max-stable extremal integrals
Recently, the notion of implicit extreme value distributions has been established, which is based on a given loss function f ≥ 0. From an application...
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Extremes of subexponential Lévy-driven random fields in the Gumbel domain of attraction
We consider a spatial Lévy-driven moving average with an underlying Lévy measure having a subexponential right tail, which is also in the maximum...
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Gaussian Random Measures Generated by Berry’s Nodal Sets
We consider vectors of random variables, obtained by restricting the length of the nodal set of Berry’s random wave model to a finite collection of...
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The relations among the notions of various kinds of stability and their applications
First, we prove that a random metric space can be isometrically embedded into a complete random normed module, as an application it is easy to see...
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System Structure Randomness and Integrity. Random Graphs Models
In this chapter the following basic questions are considered:...
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Invariant Content Representation for Generalizable Medical Image Segmentation
Domain generalization (DG) for medical image segmentation due to privacy preservation prefers learning from a single-source domain and expects good...
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Geometric Properties of Random Fields
This chapter deals with the main concepts and mathematical tools that help to describe and quantify the shapes of random fields. The geometry of...
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Multiresolution kernel matrix algebra
We propose a sparse algebra for samplet compressed kernel matrices to enable efficient scattered data analysis. We show that the compression of...
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Finding global minima via kernel approximations
We consider the global minimization of smooth functions based solely on function evaluations. Algorithms that achieve the optimal number of function...
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Multiscale Analysis of Semilinear Damped Stochastic Wave Equations
In this paper we proceed with the multiscale analysis of semilinear damped stochastic wave motions. The analysis is made by combining the well-known...
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Federated deep active learning for attention-based transaction classification
Cyber-physical transactions can be clustered and classified using an effective vector representation. Traditionally, methods for finding patterns...
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Gradient-based kernel variable selection for support vector hazards machine
This study aims to improve the predictive performance for the event time through the machine learning model and find informative variables in the...
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