Results 171 to 180 of about 2,168,026 (221)
Stochastic theory for pattern formation and front propagation in transitional pipe turbulence. [PDF]
Proc Natl Acad Sci U S AWang X, Shih HY, Goldenfeld N.
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Search model based on Kalman Filter and Monte Carlo simulation. [PDF]
PLoS OneLiu J, Li Y, Liu X.
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Development of an off-grid solar photovoltaic thermoelectric cooling system for sustainable fish preservation. [PDF]
Sci RepEl-Sebaee I +3 more
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A natural coastal blowhole as a novel wave energy extraction mechanism; experimental, cfd, and probabilistic evaluation. [PDF]
Sci RepRezaei T, Javadi A.
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Correcting Structural Bias in Dynamical Models of Infectious Disease Using a Bayesian State-Space Framework. [PDF]
Bull Math BiolAmadi M, García-Merino JC, Haario H.
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On quasi-Monte Carlo integrations
Mathematics and Computers in Simulation, 1998Relations between Monte Carlo and quasi-Monte Carlo methods are analysed from both theoretical and practical points of view with special emphasis on high-dimensional integration.
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Journal of Computational Physics, 1995
Monte Carlo methods for multidimensional integration using random (pseudo-random) and quasi-random nodes are compared both through error analysis and extensive numerical computations. Known error expressions in terms of variance, discrepancy and variation are reviewed, and the expected advantages of some quasi-random nodes (Halton, Sobol', Faure) of ...
Morokoff, William J. +1 more
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Monte Carlo methods for multidimensional integration using random (pseudo-random) and quasi-random nodes are compared both through error analysis and extensive numerical computations. Known error expressions in terms of variance, discrepancy and variation are reviewed, and the expected advantages of some quasi-random nodes (Halton, Sobol', Faure) of ...
Morokoff, William J. +1 more
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Quasi-Monte Carlo Sampling for Solving Partial Differential Equations by Deep Neural Networks
Numerical Mathematics: Theory, Methods and Applications, 2021. Solving partial differential equations in high dimensions by deep neural networks has brought significant attentions in recent years. In many scenarios, the loss function is defined as an integral over a high-dimensional domain.
Jingrun Chen
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A Quasi-Monte Carlo Method for Optimal Control Under Uncertainty
SIAM/ASA J. Uncertain. Quantification, 2021We study an optimal control problem under uncertainty, where the target function is the solution of an elliptic partial differential equation with random coefficients, steered by a control function...
Philipp A. Guth +4 more
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