Deep Learning of Subsurface Flow via Theory-guided Neural Network. - Nanzhe Wang; Dongxiao Zhang; Haibin Chang; Heng Li (CoRR, 2019)

Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network. - Nanzhe Wang; Haibin Chang; Dongxiao Zhang (CoRR, 2020)

Deep-Learning based Inverse Modeling Approaches: A Subsurface Flow Example. - Nanzhe Wang; Haibin Chang; Dongxiao Zhang (CoRR, 2020)

A Lagrangian Dual-based Theory-guided Deep Neural Network. - Miao Rong; Dongxiao Zhang; Nanzhe Wang (CoRR, 2020)

Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling. - Nanzhe Wang; Haibin Chang; Dongxiao Zhang (CoRR, 2020)

Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data. - Hao Xu; Dongxiao Zhang; Nanzhe Wang (CoRR, 2020)

Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method. - Yuntian Chen; Dou Huang; Dongxiao Zhang; Junsheng Zeng; Nanzhe Wang; Haoran Zhang; Jinyue Yan (CoRR, 2020)

Uncertainty quantification and inverse modeling for subsurface flow in 3D heterogeneous formations using a theory-guided convolutional encoder-decoder network. - Rui Xu; Dongxiao Zhang; Nanzhe Wang (CoRR, 2021)

Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method. - Yuntian Chen; Dou Huang; Dongxiao Zhang; Junsheng Zeng; Nanzhe Wang; Haoran Zhang 002; Jinyue Yan (J. Comput. Phys., 2021)

Weak form theory-guided neural network (TgNN-wf) for deep learning of subsurface single- and two-phase flow. - Rui Xu; Dongxiao Zhang; Miao Rong; Nanzhe Wang (J. Comput. Phys., 2021)

Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data. - Hao Xu 021; Dongxiao Zhang; Nanzhe Wang (J. Comput. Phys., 2021)

Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network. - Nanzhe Wang; Qinzhuo Liao; Haibin Chang; Dongxiao Zhang (CoRR, 2022)

Deep learning based closed-loop optimization of geothermal reservoir production. - Nanzhe Wang; Haibin Chang; Xiangzhao Kong; Martin O. Saar; Dongxiao Zhang (CoRR, 2022)

Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network. - Nanzhe Wang; Haibin Chang; Dongxiao Zhang (J. Comput. Phys., 2022)

Deep Learning Framework for History Matching CO2 Storage with 4D Seismic and Monitoring Well Data. - Nanzhe Wang; Louis J. Durlofsky (CoRR, 2024)