Results 71 to 80 of about 12,927,533 (245)

Multilevel Monte Carlo methods for ensemble variational data assimilation [PDF]

Nonlinear Processes in Geophysics
Ensemble variational data assimilation relies on ensembles of forecasts to estimate the background error covariance matrix B. The ensemble can be provided by an ensemble of data assimilations (EDA), which runs independent perturbed data assimilation and ...
M. Destouches, M. Destouches, M. Destouches, P. Mycek, P. Mycek, S. Gürol, S. Gürol, A. T. Weaver, A. T. Weaver, S. Gratton, E. Simon   +10 more
doaj   +1 more source

Load Distributing Metamaterials Via Discrete Optimization

Advanced Functional Materials, EarlyView.
Mechanical metamaterials are computationally optimized to homogenize transmitted forces by minimizing the spread of reaction forces. The resulting architectures transform localized loading into broader, more uniform force distributions and experimentally demonstrate robust load spreading under quasi‐static and impact loading.
Andrea Detry, Hannes Holey, Raja Zulkarnain, Roberto Guerra, Ilaria Papa, Michael Zaiser, Stefano Zapperi   +6 more
wiley   +1 more source

Random Number Generation and Monte Carlo Methods (2nd edition)

Journal of Statistical Software, 2004
s not available for ...
Rodney Sparapani
doaj   +1 more source

Designing Vanadium‐Based Oxide Electrocatalysts for Water Splitting: Experimental and Mechanistic Insights with Machine Learning

Advanced Functional Materials, EarlyView.
This review establishes structure‐property‐mechanism relationships across six modification strategies for V‐based oxide water‐splitting electrocatalysts: lattice engineering, heteroatom doping, interface engineering, carbon‐based hybridization, morphology engineering, and surface reconstruction and pre‐catalyst design, where dissolution is reframed as ...
Youness El Issmaeli, Amina Lahrichi, Hoje Chun, Rafael Gómez‐Bombarelli, Bruno G. Pollet   +4 more
wiley   +1 more source

SMCTC: Sequential Monte Carlo in C++ [PDF]

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.
Adam M. Johansen
core  

Architecture‐Driven Functional Coupling in Vertically Aligned Nanocomposites

Advanced Functional Materials, EarlyView.
Vertically aligned nanocomposites define a growth‐engineered architecture in which vertical interfaces, strain fields, defect pathways, and phase connectivity are created simultaneously. This review shows how these architectural features couple ferroic, optical, ionic, electrochemical, and device responses, establishing design rules and open challenges
Md Shatil Islam‐Shanto, Javier Zamudio‐García, Abraham Sánchez‐Caballero, David Marrero‐López, Vincenzo Esposito   +4 more
wiley   +1 more source

Monte Carlo methods for the estimation of value-at-risk and related risk measures [PDF]

, 2011
Nested Monte Carlo is a computationally expensive exercise. The main contributions we present in this thesis are the formulation of efficient algorithms to perform nested Monte Carlo for the estimation of Value-at-Risk and Expected-Tail-Loss.
Marks, Dean
core   +1 more source

Accelerated Discovery of Topological Spin Phase Diagrams in CrSBr Magnets Via High‐Throughput Optimization

Advanced Functional Materials, EarlyView.
Here, we develop a high‐throughput algorithm that accelerates the elucidation of phase diagrams of topological spin textures using limited computational resources at high numerical accuracy. Applying this framework to the van der Waals magnet CrSBr, we unveiled a hierarchy of previously unknown topological textures (domain‐wall bimerons, bimeron chains,
Andrew Lyall, Mohammad H. Badarneh, Cristian Bonato, Rebecca Cheung, Elton J. G. Santos   +4 more
wiley   +1 more source

Markov chain Monte Carlo for integrated face image analysis [PDF]

, 2014
This PhD thesis is about the integration of different methods to fit a statistical model of human faces to a single image. I propose to take a probabilistic view on the problem and implement and evaluate an integrative framework for face image ...
Schönborn, Sandro
core   +1 more source

Monte Carlo Solutions for Blind Phase Noise Estimation

EURASIP Journal on Wireless Communications and Networking, 2009
This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN) channels. The main contributions of the paper are (i) the development of a Monte Carlo framework for phase noise ...
Çırpan Hakan, Panayırcı Erdal, Simoens Frederik, Duyck Dieter, Moeneclaey Marc   +4 more
doaj   +2 more sources