Results 11 to 20 of about 512,942 (311)
Comparative Monte Carlo efficiency by Monte Carlo analysis [PDF]
Physical Review E, 2010 We propose a modified power method for computing the subdominant eigenvalue $λ_2$ of a matrix or continuous operator. Here we focus on defining simple Monte Carlo methods for its application. The methods presented use random walkers of mixed signs to represent the subdominant eigenfuction.
Rubenstein, B. M. +2 more
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2017 27th International Conference on Field Programmable Logic and Applications (FPL), 2017 Physically unclonable functions are used for IP protection, hardware authentication and supply chain security. While many PUF constructions have been put forward in the past decade, only few of them are applicable to FPGA platforms.
Rozic, Vladimir +4 more
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Statistics and Computing, 2021 Motivated mainly by applications to partial differential equations with random coefficients, we introduce a new class of Monte Carlo estimators, called Toeplitz Monte Carlo (TMC) estimator for approximating the integral of a multivariate function with respect to the direct product of an identical univariate probability measure.
Josef Dick, Takashi Goda, Hiroya Murata
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Journal of Applied Probability, 2019 AbstractIn this paper we propose a new theory and methodology to tackle the problem of unifying Monte Carlo samples from distributed densities into a single Monte Carlo draw from the target density. This surprisingly challenging problem arises in many settings (for instance, expert elicitation, multiview learning, distributed ‘big data’ problems, etc.),
Hongsheng Dai +2 more
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Error in Monte Carlo, quasi-error in Quasi-Monte Carlo [PDF]
Computer Physics Communications, 2006 While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error. The standard Monte Carlo error estimator relies on the assumption that the points are generated independently of ...
Kleiss, R.H.P., Lazopoulos, A.
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Density Estimation by Monte Carlo and Quasi-Monte Carlo
, 2022 Estimating the density of a continuous random variable X has been studied extensively in statistics, in the setting where n independent observations of X are given a priori and one wishes to estimate the density from that. Popular methods include histograms and kernel density estimators.
L'Ecuyer, P., Puchhammer, F.
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Why Monte Carlo Simulations are Inferences and not Experiments [PDF]
, 2012 Monte Carlo Simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the ...
John D. Norton +3 more
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SMCTC : sequential Monte Carlo in C++ [PDF]
, 2009 Sequential Monte Carlo methods are a very general class of Monte Carlo methods for sampling from sequences of distributions. Simple examples of these algorithms are used very widely in the tracking and signal processing literature.
Johansen, Adam M., Adam M. Johansen
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Geodesic Monte Carlo on Embedded Manifolds [PDF]
, 2013 Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows
Simon Byrne +5 more
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