Results 111 to 120 of about 2,168,026 (221)
EPJ Nuclear Sciences & Technologies, 2018 We describe an approach to calibrate Single Event Effect (SEE)-based detectors in monoenergetic fields and apply the resulting semi-empiric responses to more general mixed-field cases in which a broad variety of particle species and energy spectra are ...
Alía Rubén García +10 more
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Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models [PDF]
Hamiltonian Monte Carlo (HMC) is a recent statistical procedure to sample from complex distributions. Distant proposal draws are taken in a equence of steps following the Hamiltonian dynamics of the underlying parameter space, often yielding superior ...
John Maheu, Martin Burda
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Derivative-Variance Hybrid Global Sensitivity Measure with Optimal Sampling Method Selection
MathematicsThis paper proposes a derivative-variance hybrid global sensitivity measure with optimal sampling method selection. The proposed sensitivity measure is as computationally efficient as the derivative-based global sensitivity measure, which also serves as ...
Jiacheng Liu +5 more
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An Efficient Quasi-Monte Carlo Algorithm for High Dimensional Numerical Integration
MathematicsIn this paper, we develop a fast numerical algorithm, termed MDI-LR, for the efficient implementation of quasi-Monte Carlo lattice rules in computing d-dimensional integrals of a given function. The algorithm is based on converting the underlying lattice
Huicong Zhong, Xiaobing Feng
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Novel Strategy to Improve the Performance of Localization in WSN
The Scientific World Journal, 2015 A novel strategy of discrete energy consumption model for WSN based on quasi Monte Carlo and crude Monte Carlo method is developed. In our model the discrete hidden Markov process plays a major role in analyzing the node location in heterogeneous media ...
M. Vasim Babu, A. V. Ramprasad
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First- and quasi-second-order optimization algorithms in variational Monte Carlo
Physical Review ResearchMany quantum many-body wavefunctions, such as Jastrow-Slater, tensor network, and neural quantum states, are studied with the variational Monte Carlo technique, where stochastic optimization is usually performed to obtain a faithful approximation to the ...
Ruojing Peng, Garnet Kin-Lic Chan
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RPEM: Randomized Monte Carlo parametric expectation maximization algorithm
CPT: Pharmacometrics & Systems PharmacologyInspired from quantum Monte Carlo, by sampling discrete and continuous variables at the same time using the Metropolis–Hastings algorithm, we present a novel, fast, and accurate high performance Monte Carlo Parametric Expectation Maximization (MCPEM ...
Rong Chen +9 more
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Monte Carlo and quasi-Monte Carlo methods
Acta Numerica, 1998 R. Caflisch
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AlgorithmsMany important practical problems connected to energy efficiency in buildings, ecology, metallurgy, the development of wireless communication systems, the optimization of radar technology, quantum computing, pharmacology, and seismology are described by ...
Ivan Dimov, Rayna Georgieva
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Construction of lattice rules for multiple integration based on a weighted discrepancy [PDF]
, 2008 High-dimensional integrals arise in a variety of areas, including quantum physics, the physics and chemistry of molecules, statistical mechanics and more recently, in financial applications. In order to approximate multidimensional integrals, one may use
Sinescu, Vasile
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