Results 21 to 30 of about 2,168,026 (221)
Quasi-Monte Carlo for 3D Sliced Wasserstein [PDF]
International Conference on Learning Representations, 2023 Monte Carlo (MC) integration has been employed as the standard approximation method for the Sliced Wasserstein (SW) distance, whose analytical expression involves an intractable expectation.
Khai Nguyen, Nicola Bariletto, Nhat Ho
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Population Quasi-Monte Carlo [PDF]
Journal of Computational and Graphical Statistics, 2022 Monte Carlo methods are widely used for approximating complicated, multidimensional integrals for Bayesian inference. Population Monte Carlo (PMC) is an important class of Monte Carlo methods, which utilizes a population of proposals to generate weighted samples that approximate the target distribution.
Chaofan Huang +2 more
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MENENTUKAN HARGA OPSI DENGAN METODE MONTE CARLO BERSYARAT MENGGUNAKAN BARISAN KUASI ACAK FAURE
E-Jurnal Matematika, 2021 An option contract is a contract that gives the owner the right to sell or even to buy an asset at the predetermined price and period time. The conditional Monte Carlo is one of the several methods that is used to determine the option price which in the ...
PUTU WIDYA ASTUTI +2 more
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Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration [PDF]
Numerische Mathematik, 2022 We study the application of a tailored quasi-Monte Carlo (QMC) method to a class of optimal control problems subject to parabolic partial differential equation (PDE) constraints under uncertainty: the state in our setting is the solution of a parabolic ...
Philipp A. Guth +4 more
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Construction-free median quasi-Monte Carlo rules for function spaces with unspecified smoothness and general weights [PDF]
SIAM Journal on Scientific Computing, 2022 We study quasi-Monte Carlo (QMC) integration of smooth functions defined over the multi-dimensional unit cube. Inspired by a recent work of Pan and Owen, we study a new construction-free median QMC rule which can exploit the smoothness and the weights of
T. Goda, P. L'Ecuyer
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E-Jurnal Matematika, 2022 Estimating the value at risk (VaR) is an important aspect of investment. VaR is a standard method of measuring risk defined as the maximum loss over a certain period of time at a certain level of confidence.
PUTU SAVITRI DEVI +2 more
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Quasi-Monte Carlo Graph Random Features [PDF]
Neural Information Processing Systems, 2023 We present a novel mechanism to improve the accuracy of the recently-introduced class of graph random features (GRFs). Our method induces negative correlations between the lengths of the algorithm's random walks by imposing antithetic termination: a ...
Isaac Reid +2 more
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Inchworm quasi Monte Carlo for quantum impurities [PDF]
Physical review B, 2023 The inchworm expansion is a promising approach to solving strongly correlated quantum impurity models due to its reduction of the sign problem in real and imaginary time. However, inchworm Monte Carlo is computationally expensive, converging as 1/N where
Hugo U. R. Strand +2 more
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NEUTRONIC MODELING STRATEGIES FOR A LIQUID FUEL TRANSIENT CALCULATION [PDF]
EPJ Web of Conferences, 2021 Framework • A detailed and highly flexible numerical tool to study criticality accidents has been developed • The tool implements a Multi-Physics coupling using neutronics, thermal-hydraulics and thermal-mechanics models based on Open FOAM and SERPENT ...
Blanco J.A., Rubiolo P., Dumonteil E.
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A review of Monte Carlo and quasi‐Monte Carlo sampling techniques
WIREs Computational Statistics, 2023 This article presents a comprehensive review and comparison of the Monte Carlo and quasi‐Monte Carlo sampling techniques, which are widely used in numerical integration, simulation, and optimization.
Ying‐Chao Hung
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