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Organizational Research Methods, 2007 The study of multilevel phenomena in organizations involves a complex interplay between methods and statistics on one hand and theory development on the other. In this introduction, the authors provide a short summary of the five articles in this feature topic and use them as a platform to discuss the broad need for work in the two areas of (a ...
Paul Bliese +2 more
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MULTILEVEL CMFD ACCELERATION METHODS FOR WHOLE CORE REACTOR SIMULATION IN VERA [PDF]
EPJ Web of Conferences, 2021 Ongoing efforts are being made to improve the performance of MPACT as the deterministic neutron transport solver in the Virtual Environment for Reactor Analysis (VERA).
Cornejo Luke +2 more
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Multilevel multifidelity Monte Carlo methods for assessing uncertainty in coastal flooding [PDF]
Natural Hazards and Earth System Sciences, 2022 When choosing an appropriate hydrodynamic model, there is always a compromise between accuracy and computational cost, with high-fidelity models being more expensive than low-fidelity ones.
M. C. A. Clare +6 more
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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
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Multiple imputation methods for missing multilevel ordinal outcomes
BMC Medical Research Methodology, 2023 Background Multiple imputation (MI) is an established technique for handling missing data in observational studies. Joint modelling (JM) and fully conditional specification (FCS) are commonly used methods for imputing multilevel data. However, MI methods
Mei Dong, Aya Mitani
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Multilevel minimization for deep residual networks [PDF]
ESAIM: Proceedings and Surveys, 2021 We present a new multilevel minimization framework for the training of deep residual networks (ResNets), which has the potential to significantly reduce training time and effort.
Gaedke-Merzhäuser Lisa +2 more
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A Gradient Method for Multilevel Optimization
CoRR, 2021 Although application examples of multilevel optimization have already been discussed since the 1990s, the development of solution methods was almost limited to bilevel cases due to the difficulty of the problem. In recent years, in machine learning, Franceschi et al.
Ryo Sato, Mirai Tanaka, Akiko Takeda
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Trajectories of depressive symptoms and adult educational and employment outcomes
BJPsych Open, 2020 BackgroundDepressive symptoms show different trajectories throughout childhood and adolescence that may have different consequences for adult outcomes.AimsTo examine trajectories of childhood depressive symptoms and their association with education and ...
José A. López-López +7 more
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Multilevel modeling of diametral creep in pressure tubes of Korean CANDU units
Nuclear Engineering and Technology, 2021 : In this work, we applied a multilevel modeling technique to estimate the diametral creep in the pressure tubes of Korean Canada Deuterium Uranium (CANDU) units. Data accumulated from in-service inspections were used to develop the model. To confirm the
Gyeong-Geun Lee +4 more
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Adaptive Multilevel Krylov Methods [PDF]
ETNA - Electronic Transactions on Numerical Analysis, 2019 Summary: Inexact (variable) preconditioning of Multilevel Krylov methods (MK methods) for the solution of linear systems of equations is considered. MK methods approximate the solution of the local systems on a subspace using a few, but fixed, number of iteration steps of a preconditioned flexible Krylov method.
Kehl, René +2 more
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