Zobrazeno 1 - 10
of 919
pro vyhledávání: '"P. L'Ecuyer"'
Autor:
M. Loveless, D. Adler, F. Best, E. Borbas, X. Huang, R. Knuteson, T. L'Ecuyer, N. R. Nalli, E. Olsen, H. Revercomb, J. K. Taylor
Publikováno v:
Earth and Space Science, Vol 11, Iss 7, Pp n/a-n/a (2024)
Abstract Far infrared (FIR) emission from the Earth's polar regions has become an area of increasing scientific interest and value. FIR emission is important for understanding Earth's radiative balance and improving global climate models, especially
Externí odkaz:
https://doaj.org/article/a8bcaa0850f64a07b91da99eb2acc4a9
Reinforcement learning constantly deals with hard integrals, for example when computing expectations in policy evaluation and policy iteration. These integrals are rarely analytically solvable and typically estimated with the Monte Carlo method, whic
Externí odkaz:
http://arxiv.org/abs/2202.07808
Autor:
Goda, Takashi, L'Ecuyer, Pierre
Publikováno v:
SIAM Journal on Scientific Computing, Volume 44, Issue 4, A2765-A2788, 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 weight
Externí odkaz:
http://arxiv.org/abs/2201.09413
We introduce the R package clrng which leverages the gpuR package and is able to generate random numbers in parallel on a Graphics Processing Unit (GPU) with the clRNG (OpenCL) library. Parallel processing with GPU's can speed up computationally inte
Externí odkaz:
http://arxiv.org/abs/2201.06604
Publikováno v:
Anales de Pediatría (English Edition), Vol 101, Iss 2, Pp 73-74 (2024)
Externí odkaz:
https://doaj.org/article/dcfac6633c694be78a998709148a9814
Autor:
Fraser King, Claire Pettersen, Larry F. Bliven, Diego Cerrai, Alexey Chibisov, Steven J. Cooper, Tristan L’Ecuyer, Mark S. Kulie, Matti Leskinen, Marian Mateling, Lynn McMurdie, Dimitri Moisseev, Stephen W. Nesbitt, Walter A. Petersen, Peter Rodriguez, Carl Schirtzinger, Martin Stuefer, Annakaisa vonLerber, Matthew T. Wingo, David B. Wolff, Telyana Wong, Norman Wood
Publikováno v:
Earth and Space Science, Vol 11, Iss 5, Pp n/a-n/a (2024)
Abstract Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as
Externí odkaz:
https://doaj.org/article/165e316d25794bbe97d823795c2263c8
Autor:
L'Ecuyer, Pierre, Puchhammer, Florian
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 his
Externí odkaz:
http://arxiv.org/abs/2103.15976
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 3, Pp n/a-n/a (2024)
Abstract During the Arctic night, clouds regulate surface energy budgets through longwave warming alone. During fall, any increase in low‐level clouds will increase surface cloud warming and could potentially delay sea ice formation. While an incre
Externí odkaz:
https://doaj.org/article/f2de20d4b7f2484d93d6bc8b36171b74
We present LatNet Builder, a software tool to find good parameters for lattice rules, polynomial lattice rules, and digital nets in base 2, for quasi-Monte Carlo (QMC) and randomized quasi-Monte Carlo (RQMC) sampling over the $s$-dimensional unit hyp
Externí odkaz:
http://arxiv.org/abs/2012.10263
We explore the use of Array-RQMC, a randomized quasi-Monte Carlo method designed for the simulation of Markov chains, to reduce the variance when simulating stochastic biological or chemical reaction networks with $\tau$-leaping. The task is to estim
Externí odkaz:
http://arxiv.org/abs/2009.00337