受强制性开放获取政策约束的文章 - Adrian Sandu了解详情
无法在其他位置公开访问的文章：8 篇
Propagating uncertainty in power system dynamic simulations using polynomial chaos
Y Xu, L Mili, A Sandu, MR von Spakovsky, J Zhao
IEEE Transactions on Power Systems 34 (1), 338-348, 2018
强制性开放获取政策： US National Science Foundation
Multifidelity data assimilation for physical systems
AA Popov, A Sandu
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol …, 2022
强制性开放获取政策： US National Science Foundation
Discrete adjoint variable method for the sensitivity analysis of ALI3-P formulations
Á López Varela, C Sandu, A Sandu, D Dopico Dopico
Multibody System Dynamics, 1-22, 2023
强制性开放获取政策： Government of Spain
Rosenbrock methods with an explicit first stage
A Sandu
International Journal of Computer Mathematics 93 (6), 995-1010, 2016
强制性开放获取政策： US National Science Foundation
IMPROVING ADAM THROUGH AN IMPLICIT-EXPLICIT (IMEX) TIME-STEPPING APPROACH
A Bhattacharjee, AA Popov, A Sarshar, A Sandu
Journal of Machine Learning for Modeling and Computing 5 (3), 2024
强制性开放获取政策： US National Science Foundation, US Department of Energy
General linear methods and friends: Toward efficient solutions of multiphysics problems
A Sandu
AIP Conference Proceedings 1863 (1), 2017
强制性开放获取政策： US National Science Foundation
6.2. Application of the Generalized Polynomial Chaos to the LQR Control Problem with Uncertain Parameters in the Formulation
C Sandu, E Blanchard, A Sandu
Advanced Autonomous Vehicle Design for Severe Environments, 200-220, 2015
强制性开放获取政策： US National Aeronautics and Space Administration
6.1. Treatment of Uncertainties in Multibody Dynamic Systems using a Generalized Polynomial Chaos Approach; Case Study on a Full Vehicle
C Sandu, L Li, A Sandu
Advanced Autonomous Vehicle Design for Severe Environments, 184-199, 2015
强制性开放获取政策： US National Aeronautics and Space Administration
可在其他位置公开访问的文章：78 篇
Multirate generalized additive Runge Kutta methods
M Günther, A Sandu
Numerische Mathematik 133, 497-524, 2016
强制性开放获取政策： US National Science Foundation
Partitioned and implicit–explicit general linear methods for ordinary differential equations
H Zhang, A Sandu, S Blaise
Journal of Scientific Computing 61, 119-144, 2014
强制性开放获取政策： National Fund for Scientific Research, Belgium
A class of multirate infinitesimal GARK methods
A Sandu
SIAM Journal on Numerical Analysis 57 (5), 2300-2327, 2019
强制性开放获取政策： US National Science Foundation, US Department of Defense
Machine learning based algorithms for uncertainty quantification in numerical weather prediction models
A Moosavi, V Rao, A Sandu
Journal of Computational Science 50, 101295, 2021
强制性开放获取政策： US Department of Energy, US Department of Defense
Extrapolated implicit–explicit Runge–Kutta methods
A Cardone, Z Jackiewicz, A Sandu, H Zhang
Mathematical Modelling and Analysis 19 (1), 18-43, 2014
强制性开放获取政策： Government of Italy
A multifidelity ensemble Kalman filter with reduced order control variates
AA Popov, C Mou, A Sandu, T Iliescu
SIAM Journal on Scientific Computing 43 (2), A1134-A1162, 2021
强制性开放获取政策： US National Science Foundation, US Department of Energy
A parallel implementation of the ensemble Kalman filter based on modified Cholesky decomposition
ED Nino-Ruiz, A Sandu, X Deng
Journal of Computational Science 36, 100654, 2019
强制性开放获取政策： US National Science Foundation, US Department of Defense
An ensemble Kalman filter implementation based on modified Cholesky decomposition for inverse covariance matrix estimation
ED Nino-Ruiz, A Sandu, X Deng
SIAM Journal on Scientific Computing 40 (2), A867-A886, 2018
强制性开放获取政策： US National Science Foundation, US Department of Defense
High order implicit-explicit general linear methods with optimized stability regions
H Zhang, A Sandu, S Blaise
SIAM Journal on Scientific Computing 38 (3), A1430-A1453, 2016
强制性开放获取政策： US National Science Foundation, National Fund for Scientific Research, Belgium
Design of high-order decoupled multirate GARK schemes
A Sarshar, S Roberts, A Sandu
SIAM Journal on Scientific Computing 41 (2), A816-A847, 2019
强制性开放获取政策： US National Science Foundation, US Department of Defense
Multivariate predictions of local reduced‐order‐model errors and dimensions
A Moosavi, R Ştefănescu, A Sandu
International Journal for Numerical Methods in Engineering 113 (3), 512-533, 2018
强制性开放获取政策： US National Science Foundation, US Department of Defense
The reduced‐order hybrid Monte Carlo sampling smoother
A Attia, R Ştefănescu, A Sandu
International Journal for Numerical Methods in Fluids 83 (1), 28-51, 2017
强制性开放获取政策： US National Science Foundation, US Department of Defense
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