Zobrazeno 1 - 10
of 265
pro vyhledávání: '"GILBERT, ALEXANDER"'
In this paper, we apply quasi-Monte Carlo (QMC) methods with an initial preintegration step to estimate cumulative distribution functions and probability density functions in uncertainty quantification (UQ). The distribution and density functions cor
Externí odkaz:
http://arxiv.org/abs/2402.11807
We introduce a new Projected Rayleigh Quotient Iteration aimed at improving the convergence behaviour of classic Rayleigh Quotient iteration (RQI) by incorporating approximate information about the target eigenvector at each step. While classic RQI e
Externí odkaz:
http://arxiv.org/abs/2312.02847
Publikováno v:
ENVIRONS 2019 44:2 pp 233-272
This document is an abbreviated version of the law review, led by Alexander Q. Gilbert, entitled: "Major Federal Actions Significantly Affecting the Quality of the Space Environment: Applying NEPA to Federal and Federally Authorized Outer Space Activ
Externí odkaz:
http://arxiv.org/abs/2306.05594
Autor:
Cui, Tiangang, De Sterck, Hans, Gilbert, Alexander D., Polishchuk, Stanislav, Scheichl, Robert
We develop new multilevel Monte Carlo (MLMC) methods to estimate the expectation of the smallest eigenvalue of a stochastic convection-diffusion operator with random coefficients. The MLMC method is based on a sequence of finite element (FE) discreti
Externí odkaz:
http://arxiv.org/abs/2303.03673
In this paper we propose and analyse a method for estimating three quantities related to an Asian option: the fair price, the cumulative distribution function, and the probability density. The method involves preintegration with respect to one well c
Externí odkaz:
http://arxiv.org/abs/2212.11493
Preintegration is a technique for high-dimensional integration over $d$-dimensional Euclidean space, which is designed to reduce an integral whose integrand contains kinks or jumps to a $(d-1)$-dimensional integral of a smooth function. The resulting
Externí odkaz:
http://arxiv.org/abs/2112.11621
In this paper, we analyse a method for approximating the distribution function and density of a random variable that depends in a non-trivial way on a possibly high number of independent random variables, each with support on the whole real line. Sta
Externí odkaz:
http://arxiv.org/abs/2112.10308
We prove that a variant of the classical Sobolev space of first-order dominating mixed smoothness is equivalent (under a certain condition) to the unanchored ANOVA space on $\mathbb{R}^d$, for $d \geq 1$. Both spaces are Hilbert spaces involving weig
Externí odkaz:
http://arxiv.org/abs/2103.16075
Stochastic PDE eigenvalue problems often arise in the field of uncertainty quantification, whereby one seeks to quantify the uncertainty in an eigenvalue, or its eigenfunction. In this paper we present an efficient multilevel quasi-Monte Carlo (MLQMC
Externí odkaz:
http://arxiv.org/abs/2103.03407
Stochastic PDE eigenvalue problems are useful models for quantifying the uncertainty in several applications from the physical sciences and engineering, e.g., structural vibration analysis, the criticality of a nuclear reactor or photonic crystal str
Externí odkaz:
http://arxiv.org/abs/2010.01044