Results 241 to 250 of about 1,160,391 (297)
Investigating the Sensitivity of the Diffusion MRI Signal to Magnetization Transfer and Permeability via Monte-Carlo Simulations. [PDF]
Magn Reson MedZheng Z +3 more
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A Monte Carlo simulation study of sample size requirements for the Graded Response Model. [PDF]
PLoS OneIkeda T.
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Data-driven prediction of micro-piled raft load-settlement using machine learning and Monte Carlo simulation. [PDF]
Sci RepEl Gendy M.
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Comparison of D-Wave Quantum Annealing and Gibbs Monte Carlo for Sampling from a Probability Distribution of a Restricted Boltzmann Machine. [PDF]
Entropy (Basel)El-Yazizi A, Koshka Y.
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Machine learning enabled molecular dynamics-Monte Carlo framework for nanoconfined fluid adsorption. [PDF]
Commun ChemLiu J +7 more
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Journal of the American Statistical Association, 1949
Abstract In this paper Metropolis and Ulam gave a brief introduction to “the Monte Carlo method” which is described as a statistical approach to the study of differential equations as applied by Metropolis, Ulam, Fermi, von Neumann, Feynman, and others at the Los Alamos Laboratory in the 1940s.0 Several examples of applications of ...
N, METROPOLIS, S, ULAM
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Abstract In this paper Metropolis and Ulam gave a brief introduction to “the Monte Carlo method” which is described as a statistical approach to the study of differential equations as applied by Metropolis, Ulam, Fermi, von Neumann, Feynman, and others at the Los Alamos Laboratory in the 1940s.0 Several examples of applications of ...
N, METROPOLIS, S, ULAM
openaire +2 more sources
On Monte Carlo and Quasi-Monte Carlo for Matrix Computations
2018This paper focuses on minimizing further the communications in Monte Carlo methods for Linear Algebra and thus improving the overall performance. The focus is on producing set of small number of covering Markov chains which are much longer that the usually produced ones.
Vassil Alexandrov 0001 +5 more
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Medical Physics, 1979
The generation of long, high quality random number sequences for Monte Carlo simulations using minicomputers is considered. The importance of the thorough testing of Monte Carlo random number generators is emphasized. A recommendation is given to authors of Monte Carlo papers to specify their random number generator and to describe the randomness ...
R L, Morin +3 more
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The generation of long, high quality random number sequences for Monte Carlo simulations using minicomputers is considered. The importance of the thorough testing of Monte Carlo random number generators is emphasized. A recommendation is given to authors of Monte Carlo papers to specify their random number generator and to describe the randomness ...
R L, Morin +3 more
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SIAM Review, 2006
The probability of winning a game, set, match, or single elimination tournament in tennis is computed using Monte Carlo simulations based on each player’s probability of winning a point on serve, which can be held constant or varied from point to point, game to game, or match to match. The theory, described in Newton and Keller [Stud. Appl. Math., 114 (
Paul K. Newton, Kamran Aslam
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The probability of winning a game, set, match, or single elimination tournament in tennis is computed using Monte Carlo simulations based on each player’s probability of winning a point on serve, which can be held constant or varied from point to point, game to game, or match to match. The theory, described in Newton and Keller [Stud. Appl. Math., 114 (
Paul K. Newton, Kamran Aslam
openaire +1 more source