Nanzhe Wang
Orcid: 0000-0002-5177-946X
According to our database1,
Nanzhe Wang authored at least 16 papers
between 2019 and 2026.
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Bibliography
2026
AutoSurrogate: An LLM-Driven Multi-Agent Framework for Autonomous Construction of Deep Learning Surrogate Models in Subsurface Flow.
CoRR, April, 2026
Machine learning for sustainable geoenergy: uncertainty, physics and decision-ready inference.
CoRR, March, 2026
2024
Deep Learning Framework for History Matching CO2 Storage with 4D Seismic and Monitoring Well Data.
CoRR, 2024
2022
Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network.
J. Comput. Phys., 2022
CoRR, 2022
Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network.
CoRR, 2022
Complex Intell. Syst., 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
Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data.
CoRR, 2020
CoRR, 2020
CoRR, 2020
Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network.
CoRR, 2020
2019