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Subhayan De
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On transfer learning of neural networks using bi-fidelity data for uncertainty propagation
S De, J Britton, M Reynolds, R Skinner, K Jansen, A Doostan
International Journal for Uncertainty Quantification 10 (6), 2020
622020
Topology optimization under uncertainty using a stochastic gradient-based approach
S De, J Hampton, K Maute, A Doostan
Structural and Multidisciplinary Optimization 62, 2255-2278, 2020
422020
Bi-fidelity modeling of uncertain and partially unknown systems using deeponets
S De, M Reynolds, M Hassanaly, RN King, A Doostan
arXiv preprint arXiv:2204.00997, 2022
302022
Neural network training using ℓ1-regularization and bi-fidelity data
S De, A Doostan
Journal of Computational Physics 458, 111010, 2022
242022
Bi-fidelity stochastic gradient descent for structural optimization under uncertainty
S De, K Maute, A Doostan
Computational Mechanics 66, 745-771, 2020
242020
Efficient optimal design and design‐under‐uncertainty of passive control devices with application to a cable‐stayed bridge
S De, SF Wojtkiewicz, EA Johnson
Structural Control and Health Monitoring 24 (2), e1846, 2017
212017
Reliability-based topology optimization using stochastic gradients
S De, K Maute, A Doostan
Structural and Multidisciplinary Optimization 64 (5), 3089-3108, 2021
102021
Investigation of model falsification using error and likelihood bounds with application to a structural system
S De, PT Brewick, EA Johnson, SF Wojtkiewicz
Journal of Engineering Mechanics 144 (9), 04018078, 2018
92018
Computationally efficient Bayesian model selection for locally nonlinear structural dynamic systems
S De, EA Johnson, SF Wojtkiewicz, PT Brewick
Journal of Engineering Mechanics 144 (5), 04018022, 2018
92018
A hybrid probabilistic framework for model validation with application to structural dynamics modeling
S De, PT Brewick, EA Johnson, SF Wojtkiewicz
Mechanical Systems and Signal Processing 121, 961-980, 2019
82019
Uncertainty quantification of locally nonlinear dynamical systems using neural networks
S De
Journal of Computing in Civil Engineering 35 (4), 04021009, 2021
62021
Fast Bayesian model selection with application to large locally-nonlinear dynamic systems
S De, EA Johnson, SF Wojtkiewicz
Proc., 6th Int. Conf. on Advances in Experimental Structural Engineering …, 2015
32015
Bi-fidelity variational auto-encoder for uncertainty quantification
N Cheng, OA Malik, S De, S Becker, A Doostan
Computer Methods in Applied Mechanics and Engineering 421, 116793, 2024
22024
Topology optimization under microscale uncertainty using stochastic gradients
S De, K Maute, A Doostan
Structural and Multidisciplinary Optimization 66 (1), 17, 2023
22023
Prediction of Ultrasonic Guided Wave Propagation in Fluid–Structure and Their Interface under Uncertainty Using Machine Learning
S De, BSM Ebna Hai, A Doostan, M Bause
Journal of Engineering Mechanics 148 (3), 04021161, 2022
22022
Efficient Bayesian model selection for identifying locally nonlinear systems incorporating dynamic measurements
S De, EA Johnson, SF Wojtkiewicz, PT Brewick
Structural Health Monitoring 2015, 2015
22015
Efficient optimal design-under-uncertainty of passive structural control devices
S De, SF Wojtkiewicz, EA Johnson
22015
PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model
M Hassanaly, PJ Weddle, RN King, S De, A Doostan, CR Randall, ...
arXiv preprint arXiv:2312.17329, 2023
12023
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model
M Hassanaly, PJ Weddle, RN King, S De, A Doostan, CR Randall, ...
arXiv preprint arXiv:2312.17336, 2023
2023
A Bi-fidelity DeepONet Approach for Modeling Uncertain and Degrading Hysteretic Systems
S De, PT Brewick
arXiv preprint arXiv:2304.12609, 2023
2023
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