Nanzhe Wang

Orcid: 0000-0002-5177-946X

According to our database1, Nanzhe Wang authored at least 12 papers between 2019 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

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PhD thesis 
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Links

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Bibliography

2022
Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network.
J. Comput. Phys., 2022

Deep learning based closed-loop optimization of geothermal reservoir production.
CoRR, 2022

Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network.
CoRR, 2022

2021
Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data.
J. Comput. Phys., 2021

Weak form theory-guided neural network (TgNN-wf) for deep learning of subsurface single- and two-phase flow.
J. Comput. Phys., 2021

Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method.
J. Comput. Phys., 2021

Uncertainty quantification and inverse modeling for subsurface flow in 3D heterogeneous formations using a theory-guided convolutional encoder-decoder network.
CoRR, 2021

2020
Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling.
CoRR, 2020

A Lagrangian Dual-based Theory-guided Deep Neural Network.
CoRR, 2020

Deep-Learning based Inverse Modeling Approaches: A Subsurface Flow Example.
CoRR, 2020

Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network.
CoRR, 2020

2019
Deep Learning of Subsurface Flow via Theory-guided Neural Network.
CoRR, 2019


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