Results 21 to 30 of about 700,908 (311)
Comparison of three recent discrete stochastic inversion methods and influence of the prior choice
Comptes Rendus. Géoscience, 2022 Groundwater flow depends on subsurface heterogeneity, which often calls for categorical fields to represent different geological facies. The knowledge about subsurface is however limited and often provided indirectly by state variables, such as hydraulic
Juda, Przemysław +2 more
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EURASIP Journal on Information Security, 2020 In recent years, classification techniques based on deep neural networks (DNN) were widely used in many fields such as computer vision, natural language processing, and self-driving cars. However, the vulnerability of the DNN-based classification systems
Olga Taran +3 more
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Computer Sciences & Mathematics Forum, 2023 In this paper, we propose a non-parametric estimator of the conditional hazard function weighted on the recursive kernel method given an explanatory variable taking values in a semi-metric space when the scalar response is censored.
Hadjer Kebir, Boubaker Mechab
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A Theory of Stochastic Harvesting in Stochastic Environments [PDF]
The American Naturalist, 2002 We investigate how model populations respond to stochastic harvesting in a stochastic environment. In particular, we show that the effects of variable harvesting on the variance in population density and yield depend critically on the autocorrelation of environmental noise and on whether the endogenous dynamics of the population display over- or ...
Jonzén, Niclas +2 more
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Information Bottleneck Classification in Extremely Distributed Systems
Entropy, 2020 We present a new decentralized classification system based on a distributed architecture. This system consists of distributed nodes, each possessing their own datasets and computing modules, along with a centralized server, which provides probes to ...
Denis Ullmann +5 more
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The distance spectrum of two new operations of graphs [PDF]
Transactions on Combinatorics, 2020 Let $G$ be a connected graph with vertex set $V(G)=\{v_1, v_2,\ldots,v_n\}$. The distance matrix $D=D(G)$ of $G$ is defined so that its $(i,j)$-entry is equal to the distance $d_G(v_i,v_j)$ between the vertices $v_i$ and $v_j$ of $G$. The eigenvalues
Zikai Tang +3 more
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Local linear modelling of the conditional distribution function for functional ergodic data
Mathematical Modelling and Analysis, 2022 The focus of functional data analysis has been mostly on independent functional observations. It is therefore hoped that the present contribution will provide an informative account of a useful approach that merges the ideas of the ergodic theory and ...
Somia Ayad +3 more
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A posteriori error estimation for stochastic static problems [PDF]
, 2014 To solve stochastic static field problems, a discretization by the Finite Element Method can be used. A system of equations is obtained with the unknowns (scalar potential at nodes for example) being random variables. To solve this stochastic system, the
MAC, Hung, CLENET, Stephane
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Water Resources Research, 2023 Bayesian model selection (BMS) and Bayesian model justifiability analysis (BMJ) provide a statistically rigorous framework for comparing competing models through the use of Bayesian model evidence (BME).
Maria Fernanda Morales Oreamuno +2 more
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Applied Computing and Geosciences, 2022 Multiple-point statistics algorithms allow modeling spatial variability from training images. Among these techniques, the Direct Sampling (DS) algorithm has advanced capabilities, such as multivariate simulations, treatment of non-stationarity, multi ...
Przemysław Juda +2 more
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