Kamu erişimi zorunlu olan makaleler - Michael D. ShieldsDaha fazla bilgi edinin
Hiçbir yerde sunulmuyor: 4
On the influence of over-parameterization in manifold based surrogates and deep neural operators
K Kontolati, S Goswami, MD Shields, GE Karniadakis
Journal of Computational Physics 479, 112008, 2023
Zorunlu olanlar: US Department of Energy, US Department of Defense
Simulation of wind velocity time histories on long span structures modeled as non-Gaussian stochastic waves
H Zhou, G Deodatis, M Shields, B Benowitz
Probabilistic Engineering Mechanics 59, 103016, 2020
Zorunlu olanlar: National Natural Science Foundation of China
Efficient Uncertainty Propagation for High-Fidelity Simulations With Large Parameter Spaces: Application to Stiffened Plate Buckling
K Nahshon, N Reynolds, MD Shields
Journal of Verification, Validation, and Uncertainty Quantification 3, 011003, 2018
Zorunlu olanlar: US Department of Defense
Direct Simulation Methods for a Class of Normal and Lognormal Random Fields with Applications in Modeling Material Properties
PP Fang, Y Liu, MD Shields
Journal of Engineering Mechanics 148 (2), 04021146, 2022
Zorunlu olanlar: National Natural Science Foundation of China
Bir yerde sunuluyor: 42
Bayesian neural networks for uncertainty quantification in data-driven materials modeling
A Olivier, MD Shields, L Graham-Brady
Computer Methods in Applied Mechanics and Engineering 386, 114079, 2021
Zorunlu olanlar: US Department of Defense
On the quantification and efficient propagation of imprecise probabilities resulting from small datasets
J Zhang, MD Shields
Mechanical Systems and Signal Processing 98, 465-483, 2018
Zorunlu olanlar: US Department of Defense
Deep transfer operator learning for partial differential equations under conditional shift
S Goswami, K Kontolati, MD Shields, GE Karniadakis
Nature Machine Intelligence 4 (12), 1155-1164, 2022
Zorunlu olanlar: US Department of Energy, US Department of Defense
UQpy: A general purpose Python package and development environment for uncertainty quantification
A Olivier, D Giovanis, BS Aakash, M Chauhan, L Vandanapu, MD Shields
Journal of Computational Science 47, 101204, 2020
Zorunlu olanlar: US National Science Foundation, US Department of Energy, US Department of …
Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold
DG Giovanis, MD Shields
Computer Methods in Applied Mechanics and Engineering 370, 113269, 2020
Zorunlu olanlar: US Department of Energy
Topology optimization for linear stationary stochastic dynamics: Applications to frame structures
M Zhu, Y Yang, JK Guest, MD Shields
Structural Safety 67, 116-131, 2017
Zorunlu olanlar: US National Science Foundation
Coarse graining atomistic simulations of plastically deforming amorphous solids
AR Hinkle, CH Rycroft, MD Shields, ML Falk
Physical Review E 95 (5), 053001, 2017
Zorunlu olanlar: US National Science Foundation, US Department of Energy
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems
K Kontolati, D Loukrezis, DG Giovanis, L Vandanapu, MD Shields
Journal of Computational Physics 464, 111313, 2022
Zorunlu olanlar: US Department of Energy, German Research Foundation
The effect of prior probabilities on quantification and propagation of imprecise probabilities resulting from small datasets
J Zhang, MD Shields
Computer Methods in Applied Mechanics and Engineering 334, 483-506, 2018
Zorunlu olanlar: US Department of Defense
Adaptive Monte Carlo analysis for strongly nonlinear stochastic systems
MD Shields
Reliability Engineering & System Safety 175, 207-224, 2018
Zorunlu olanlar: US National Science Foundation, US Department of Defense
Active learning with multifidelity modeling for efficient rare event simulation
SLN Dhulipala, MD Shields, BW Spencer, C Bolisetti, AE Slaughter, ...
Journal of Computational Physics 468, 111506, 2022
Zorunlu olanlar: US Department of Energy
Deep transfer learning for partial differential equations under conditional shift with DeepONet
S Goswami, K Kontolati, MD Shields, GE Karniadakis
arXiv preprint arXiv:2204.09810 55, 2022
Zorunlu olanlar: US Department of Energy, US Department of Defense
Topology optimization of continuum structures subjected to filtered white noise stochastic excitations
Y Yang, M Zhu, MD Shields, JK Guest
Computer Methods in Applied Mechanics and Engineering 324, 438-456, 2017
Zorunlu olanlar: US National Science Foundation
Stochastic collocation approach with adaptive mesh refinement for parametric uncertainty analysis
A Bhaduri, Y He, MD Shields, L Graham-Brady, RM Kirby
Journal of Computational Physics 371, 732-750, 2018
Zorunlu olanlar: US Department of Defense
Imprecise global sensitivity analysis using bayesian multimodel inference and importance sampling
J Zhang, S TerMaath, MD Shields
Mechanical Systems and Signal Processing 148, 107162, 2021
Zorunlu olanlar: US Department of Energy, US Department of Defense
On the usefulness of gradient information in surrogate modeling: Application to uncertainty propagation in composite material models
A Bhaduri, D Brandyberry, MD Shields, P Geubelle, L Graham-Brady
Probabilistic Engineering Mechanics 60, 103024, 2020
Zorunlu olanlar: US Department of Defense
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