Artikel dengan mandat akses publik - Akil NarayanPelajari lebih lanjut
Tidak tersedia di mana pun: 1
Robust topology optimization with low rank approximation using artificial neural networks
V Keshavarzzadeh, RM Kirby, A Narayan
Computational Mechanics 68 (6), 1297-1323, 2021
Mandat: US Department of Defense
Tersedia di suatu tempat: 87
Adaptive Leja sparse grid constructions for stochastic collocation and high-dimensional approximation
A Narayan, JD Jakeman
SIAM Journal on Scientific Computing 36 (6), A2952-A2983, 2014
Mandat: US Department of Energy
Polynomial chaos expansions for dependent random variables
JD Jakeman, F Franzelin, A Narayan, M Eldred, D Plfüger
Computer Methods in Applied Mechanics and Engineering 351, 643-666, 2019
Mandat: US National Science Foundation, US Department of Energy, US Department of …
A Christoffel function weighted least squares algorithm for collocation approximations
A Narayan, J Jakeman, T Zhou
Mathematics of Computation 86 (306), 1913-1947, 2017
Mandat: US Department of Energy, US Department of Defense, Chinese Academy of …
A generalized sampling and preconditioning scheme for sparse approximation of polynomial chaos expansions
JD Jakeman, A Narayan, T Zhou
SIAM Journal on Scientific Computing 39 (3), A1114-A1144, 2017
Mandat: US Department of Energy, US Department of Defense, Chinese Academy of …
Numerical integration in multiple dimensions with designed quadrature
V Keshavarzzadeh, RM Kirby, A Narayan
SIAM Journal on Scientific Computing 40 (4), A2033-A2061, 2018
Mandat: US Department of Defense
Flexibility reserve in power systems: Definition and stochastic multi-fidelity optimization
R Khatami, M Parvania, A Narayan
IEEE Transactions on Smart Grid 11 (1), 644-654, 2019
Mandat: US Department of Energy
Effectively subsampled quadratures for least squares polynomial approximations
P Seshadri, A Narayan, S Mahadevan
SIAM/ASA Journal on Uncertainty Quantification 5 (1), 1003-1023, 2017
Mandat: US Department of Defense, US National Institutes of Health, UK Engineering …
Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction
J Hampton, HR Fairbanks, A Narayan, A Doostan
Journal of Computational Physics 368, 315-332, 2018
Mandat: US National Science Foundation, US Department of Energy, US Department of …
Stochastic collocation on unstructured multivariate meshes
A Narayan, T Zhou
Communications in Computational Physics 18 (1), 1-36, 2015
Mandat: National Natural Science Foundation of China
A gradient enhanced ℓ1-minimization for sparse approximation of polynomial chaos expansions
L Guo, A Narayan, T Zhou
Journal of Computational Physics 367, 49-64, 2018
Mandat: US Department of Defense, National Natural Science Foundation of China
Constructing least-squares polynomial approximations
L Guo, A Narayan, T Zhou
SIAM Review 62 (2), 483-508, 2020
Mandat: US National Science Foundation, US Department of Defense, Chinese Academy of …
A metalearning approach for physics-informed neural networks (PINNs): Application to parameterized PDEs
M Penwarden, S Zhe, A Narayan, RM Kirby
Journal of Computational Physics 477, 111912, 2023
Mandat: US Department of Defense
Multifidelity modeling for physics-informed neural networks (pinns)
M Penwarden, S Zhe, A Narayan, RM Kirby
Journal of Computational Physics 451, 110844, 2022
Mandat: US Department of Defense
Weighted discrete least-squares polynomial approximation using randomized quadratures
T Zhou, A Narayan, D Xiu
Journal of Computational Physics 298, 787-800, 2015
Mandat: US Department of Energy, National Natural Science Foundation of China
Multivariate discrete least-squares approximations with a new type of collocation grid
T Zhou, A Narayan, Z Xu
SIAM Journal on Scientific Computing 36 (5), A2401-A2422, 2014
Mandat: National Natural Science Foundation of China
RBF-LOI: Augmenting radial basis functions (RBFs) with least orthogonal interpolation (LOI) for solving PDEs on surfaces
V Shankar, A Narayan, RM Kirby
Journal of Computational Physics 373, 722-735, 2018
Mandat: US National Science Foundation, US Department of Defense
Parametric topology optimization with multiresolution finite element models
V Keshavarzzadeh, RM Kirby, A Narayan
International Journal for Numerical Methods in Engineering 119 (7), 567-589, 2019
Mandat: US National Science Foundation, US Department of Defense
Weighted approximate Fekete points: sampling for least-squares polynomial approximation
L Guo, A Narayan, L Yan, T Zhou
SIAM Journal on Scientific Computing 40 (1), A366-A387, 2018
Mandat: US National Science Foundation, US Department of Defense, Chinese Academy of …
A robust hyperviscosity formulation for stable RBF-FD discretizations of advection-diffusion-reaction equations on manifolds
V Shankar, GB Wright, A Narayan
SIAM Journal on Scientific Computing 42 (4), A2371-A2401, 2020
Mandat: US National Science Foundation, US Department of Defense
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