Mengwu Guo
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- 2022
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Mark
Deep kernel learning of dynamical models from high-dimensional noisy data
- Contribution to journal › Article
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Mark
Predictive Monitoring of Large-Scale Engineering Assets Using Machine Learning Techniques and Reduced-Order Modeling
- Chapter in Book/Report/Conference proceeding › Book chapter
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Mark
Energy-Based Error Bound of Physics-Informed Neural Network Solutions in Elasticity
- Contribution to journal › Article
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Mark
Multi-fidelity regression using artificial neural networks : Efficient approximation of parameter-dependent output quantities
- Contribution to journal › Article
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Mark
Bayesian operator inference for data-driven reduced-order modeling
- Contribution to journal › Article
- 2021
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Mark
A brief note on understanding neural networks as Gaussian processes
(2021)
- Working paper/Preprint › Preprint in preprint archive
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Mark
Uncertainty quantification for physics-informed deep learning
(2021) p.47-51
- Chapter in Book/Report/Conference proceeding › Chapter in report
- 2020
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Mark
A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems
- Contribution to journal › Article
- 2019
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Mark
Non-intrusive reduced-order modeling for fluid problems : A brief review
(2019) In Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233(16). p.5896-5912
- Contribution to journal › Scientific review
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Mark
Data-driven reduced order modeling for time-dependent problems
- Contribution to journal › Article