Follow
Subhayan De
Title
Cited by
Cited by
Year
Topology optimization under uncertainty using a stochastic gradient-based approach
S De, J Hampton, K Maute, A Doostan
Structural and Multidisciplinary Optimization 62 (5), 2255-2278, 2020
272020
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
242020
Bi-fidelity stochastic gradient descent for structural optimization under uncertainty
S De, K Maute, A Doostan
Computational Mechanics 66 (4), 745-771, 2020
182020
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
182017
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), 2018
72018
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
62019
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
62018
Reliability-based topology optimization using stochastic gradients
S De, K Maute, A Doostan
Structural and Multidisciplinary Optimization 64 (5), 3089-3108, 2021
42021
Neural Network Training Using -Regularization and Bi-fidelity Data
S De, A Doostan
arXiv preprint arXiv:2105.13011, 2021
4*2021
Fast Bayesian model selection with application to large locally-nonlinear dynamic systems
S De, EA Johnson, SF Wojtkiewicz
6th International Conference on Advances in Experimental Structural …, 2015
32015
Uncertainty quantification of locally nonlinear dynamical systems using neural networks
S De
arXiv preprint arXiv:2008.04598, 2020
22020
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
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets
S De, M Hassanaly, M Reynolds, RN King, A Doostan
arXiv preprint arXiv:2204.00997, 2022
12022
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
12022
Topology Optimization under Microscale Uncertainty using Stochastic Gradients
S De, K Maute, A Doostan
arXiv preprint arXiv:2110.13358, 2021
2021
Prediction of ultrasonic guided wave propagation in solid-fluid and their interface under uncertainty using machine learning
S De, BSME Hai, A Doostan, M Bause
arXiv preprint arXiv:2105.02813, 2021
2021
MODEL VALIDATION OF A FOUR-STORY BASE ISOLATED BUILDING USING MEASUREMENTS FROM SEISMIC SHAKE-TABLE EXPERIMENTS
S De, T Yu, EA Johnson, SF Wojtkiewicz
2018
Investigation of Model Falsification Using Error and Likelihood Bounds with Application to a Structural System
D Subhayan, T Brewick Patrick, A Johnson Erik
American Society of Civil Engineers, 2018
2018
A Novel Hybrid Probabilistic Framework for Model Validation
S De
University of Southern California, 2018
2018
The system can't perform the operation now. Try again later.
Articles 1–20