Abstract: Through the radio map presented by the signal strength at observed points, the signal distributions such as signal attenuation of an area can be obtained. However, it is practically ...
We introduce an approach for efficient Markov chain Monte Carlo (MCMC) sampling for challenging high-dimensional distributions in sparse Bayesian learning (SBL). The core innovation involves using ...
One of the main obstacles to the routine implementation of Bayesian methods has been the absence of efficient algorithms for carrying out the computational tasks implicit in the Bayesian approach. In ...
Oil spills can be among the most devastating environmental disasters, with the potential to severely damage marine ecosystems ...
SIAM Journal on Numerical Analysis, Vol. 48, No. 1 (2010), pp. 322-345 (24 pages) Inverse problems are often ill posed, with solutions that depend sensitively on data. In any numerical approach to the ...
Abstract: In order to use Bayesian network for a complex world, this paper proposes a framework to simplify the network structure. The framework consists of ¿elimination¿, ¿segmentation¿ and ...
Parameter estimation in differential equation models is a critical endeavour in the mathematical modelling of dynamic systems. Such models, represented by ordinary differential equations (ODEs), ...
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