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A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Journal of hydrology (Amsterdam), 2024-06, Vol.636 (C), Article 131219

2024

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A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Journal of hydrology (Amsterdam), 2024-04, Vol.636 (1)

2024

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Gaussian process regression and conditional Karhunen-Loève models for data assimilation in inverse problems

Journal of computational physics, 2024-04, Vol.502 (C), p.112788, Article 112788

2024

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Physics-informed machine learning method with space-time Karhunen-Loève expansions for forward and inverse partial differential equations

Journal of computational physics, 2024-02, Vol.499, p.112723, Article 112723

2024

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Conditional Karhunen–Loève regression model with Basis Adaptation for high-dimensional problems: Uncertainty quantification and inverse modeling

Computer methods in applied mechanics and engineering, 2024-01, Vol.418 (PA), p.116487, Article 116487

2024

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Conditional Karhunen–Loève regression model with Basis Adaptation for high-dimensional problems: Uncertainty quantification and inverse modeling

Computer methods in applied mechanics and engineering, 2023-10, Vol.418

2023

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Improved training of physics-informed neural networks for parabolic differential equations with sharply perturbed initial conditions

Computer methods in applied mechanics and engineering, 2023-09, Vol.414 (C), p.116125, Article 116125

2023

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Physics-informed Gaussian process regression for states estimation and forecasting in power grids

International journal of forecasting, 2023-04, Vol.39 (2), p.967-980

2023

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Urban Flood Modeling: Uncertainty Quantification and Physics‐Informed Gaussian Processes Regression Forecasting

Water resources research, 2023-03, Vol.59 (3), p.n/a

2023

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Physics-informed CoKriging model of a redox flow battery

Journal of power sources, 2022-09, Vol.542, p.231668, Article 231668

2022

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Physics-informed Karhunen-Loéve and neural network approximations for solving inverse differential equation problems

Journal of computational physics, 2022-08, Vol.462 (C), p.111230, Article 111230

2022

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Physics‐Informed Machine Learning Method for Large‐Scale Data Assimilation Problems

Water resources research, 2022-05, Vol.58 (5)

2022

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Physics‐Informed Machine Learning Method for Large‐Scale Data Assimilation Problems

Water resources research, 2022-05, Vol.58 (5), p.n/a

2022

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Physics-constrained deep neural network method for estimating parameters in a redox flow battery

Journal of power sources, 2022-04, Vol.528, p.231147, Article 231147

2022

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Physics-informed Karhunen-Loeve and Neural Network Approximations for Solving Inverse Differential Equation Problems

Journal of computational physics, 2022-04, Vol.462

2022

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Stochastically Forced Ensemble Dynamic Mode Decomposition for Forecasting and Analysis of Near-Periodic Systems

IEEE access, 2022, Vol.10, p.33440-33448

2022

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Learning viscoelasticity models from indirect data using deep neural networks

Computer methods in applied mechanics and engineering, 2021-12, Vol.387 (C), p.114124, Article 114124

2021

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Learning viscoelasticity models from indirect data using deep neural networks

Computer methods in applied mechanics and engineering, 2021-12, Vol.387

2021

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Physics‐Informed Neural Network Method for Forward and Backward Advection‐Dispersion Equations

Water resources research, 2021-07, Vol.57 (7), p.n/a

2021

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Numerical and Analytical Modeling of Flow Partitioning in Partially Saturated Fracture Networks

Water resources research, 2021-04, Vol.57 (4), p.n/a

2021

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A conservative level set method for N-phase flows with a free-energy-based surface tension model

Journal of computational physics, 2021-02, Vol.426 (C), p.109955, Article 109955

2021

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Physics Information Aided Kriging using Stochastic Simulation Models

SIAM journal on scientific computing, 2021-01, Vol.43 (6), p.A3862-A3891

2021

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Non-local model for surface tension in fluid-fluid simulations

Journal of computational physics, 2020-11, Vol.421, p.109732, Article 109732

2020

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Non-local model for surface tension in fluid-fluid simulations

Journal of computational physics, 2020-11, Vol.421 (C)

2020

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Explaining persistent incomplete mixing in multicomponent reactive transport with Eulerian stochastic model

Advances in water resources, 2020-11, Vol.145 (C), p.103729, Article 103729

2020

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A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Gaussian process regression and conditional Karhunen-Loève models for data assimilation in inverse problems

Physics-informed machine learning method with space-time Karhunen-Loève expansions for forward and inverse partial differential equations

Conditional Karhunen–Loève regression model with Basis Adaptation for high-dimensional problems: Uncertainty quantification and inverse modeling

Conditional Karhunen–Loève regression model with Basis Adaptation for high-dimensional problems: Uncertainty quantification and inverse modeling

Improved training of physics-informed neural networks for parabolic differential equations with sharply perturbed initial conditions

Physics-informed Gaussian process regression for states estimation and forecasting in power grids

Urban Flood Modeling: Uncertainty Quantification and Physics‐Informed Gaussian Processes Regression Forecasting

Physics-informed CoKriging model of a redox flow battery

Physics-informed Karhunen-Loéve and neural network approximations for solving inverse differential equation problems

Physics‐Informed Machine Learning Method for Large‐Scale Data Assimilation Problems

Physics‐Informed Machine Learning Method for Large‐Scale Data Assimilation Problems

Physics-constrained deep neural network method for estimating parameters in a redox flow battery

Physics-informed Karhunen-Loeve and Neural Network Approximations for Solving Inverse Differential Equation Problems

Stochastically Forced Ensemble Dynamic Mode Decomposition for Forecasting and Analysis of Near-Periodic Systems

Learning viscoelasticity models from indirect data using deep neural networks

Learning viscoelasticity models from indirect data using deep neural networks

Physics‐Informed Neural Network Method for Forward and Backward Advection‐Dispersion Equations

Numerical and Analytical Modeling of Flow Partitioning in Partially Saturated Fracture Networks

A conservative level set method for N-phase flows with a free-energy-based surface tension model

Physics Information Aided Kriging using Stochastic Simulation Models

Non-local model for surface tension in fluid-fluid simulations

Non-local model for surface tension in fluid-fluid simulations

Explaining persistent incomplete mixing in multicomponent reactive transport with Eulerian stochastic model

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