Results 1 to 10 of about 2,168,026 (221)
An efficient quasi-Monte Carlo method with forced fixed detection for photon scatter simulation in CT [PDF]
PLoS ONE, 2023 Detected scattered photons can cause cupping and streak artifacts, significantly degrading the quality of CT images. For fast and accurate estimation of scatter intensities resulting from photon interactions with a phantom, we first transform the path ...
Guiyuan Lin, Shiwo Deng, Xiaoqun Wang
doaj +3 more sources
Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media [PDF]
Royal Society Open Science, 2017 In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during ...
D. Crevillén-García, H. Power
doaj +2 more sources
A universal median quasi-Monte Carlo integration [PDF]
SIAM Journal on Numerical Analysis, 2022 We study quasi-Monte Carlo (QMC) integration over the multi-dimensional unit cube in several weighted function spaces with different smoothness classes.
Takashi Goda +2 more
semanticscholar +6 more sources
Quasi-Monte Carlo Methods in Python
Journal of Open Source Software, 2023 NumPy random number generators and SciPy distributions are widely used to generate random numbers. However, challenges might arise when sampling in high dimensions. Quasi-Monte Carlo (QMC) methods provide an answer to these problems but are arguably hard
Pamphile T. Roy +3 more
semanticscholar +3 more sources
Quasi-Monte Carlo Software [PDF]
Monte Carlo and Quasi-Monte Carlo Methods, 2021 Practitioners wishing to experience the efficiency gains from using low discrepancy sequences need correct, robust, well-written software. This article, based on our MCQMC 2020 tutorial, describes some of the better quasi-Monte Carlo (QMC) software ...
Sou-Cheng T. Choi +4 more
semanticscholar +4 more sources
Fast uncertainty quantification of tracer distribution in the brain interstitial fluid with multilevel and quasi Monte Carlo. [PDF]
Int J Numer Method Biomed Eng, 2021 Efficient uncertainty quantification algorithms are key to understand the propagation of uncertainty—from uncertain input parameters to uncertain output quantities—in high resolution mathematical models of brain physiology.
Croci M, Vinje V, Rognes ME.
europepmc +3 more sources
Sequential Quasi Monte Carlo [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2015 SummaryWe derive and study sequential quasi Monte Carlo (SQMC), a class of algorithms obtained by introducing QMC point sets in particle filtering. SQMC is related to, and may be seen as an extension of, the array-RQMC algorithm of L'Ecuyer and his colleagues. The complexity of SQMC is O{Nlog(N)}, where N is the number of simulations at each iteration,
Mathieu Gerber, Nicolas Chopin
exaly +5 more sources
Advances in Neural Information Processing Systems 36, 2023 Langevin Monte Carlo (LMC) and its stochastic gradient versions are powerful algorithms for sampling from complex high-dimensional distributions. To sample from a distribution with density $\pi(\theta)\propto \exp(-U(\theta)) $, LMC iteratively generates
Sifan Liu
semanticscholar +4 more sources
A Quasi-Monte Carlo Method Based on Neural Autoregressive Flow [PDF]
EntropyThis paper proposes a novel transport quasi-Monte Carlo framework that combines randomized quasi-Monte Carlo sampling with a neural autoregressive flow architecture for efficient sampling and integration over complex, high-dimensional distributions.
Yunfan Wei, Wei Xi
doaj +2 more sources
SIAM Journal on Scientific ComputingQuasi-Monte Carlo (QMC) is a powerful method for evaluating high-dimensional integrals. However, its use is typically limited to distributions where direct sampling is straightforward, such as the uniform distribution on the unit hypercube or the ...
Sifan Liu
semanticscholar +4 more sources