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2020 – today
- 2022
[j5]Nanzhe Wang
, Haibin Chang, Dongxiao Zhang:
Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network. J. Comput. Phys. 466: 111419 (2022)- [i12]Nanzhe Wang, Qinzhuo Liao, Haibin Chang, Dongxiao Zhang:
Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network. CoRR abs/2201.00698 (2022) - [i11]Nanzhe Wang, Haibin Chang, Xiangzhao Kong, Martin O. Saar, Dongxiao Zhang:
Deep learning based closed-loop optimization of geothermal reservoir production. CoRR abs/2204.08987 (2022) - [i10]Tianhao He, Haibin Chang, Dongxiao Zhang:
Identification of Physical Processes and Unknown Parameters of 3D Groundwater Contaminant Problems via Theory-guided U-net. CoRR abs/2205.00134 (2022) - 2021
- [i9]Nanzhe Wang, Haibin Chang, Dongxiao Zhang:
Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network. CoRR abs/2110.10080 (2021) - 2020
- [j4]Hao Xu, Haibin Chang, Dongxiao Zhang:
DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm. J. Comput. Phys. 418: 109584 (2020) - [i8]Hao Xu, Haibin Chang, Dongxiao Zhang:
DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm. CoRR abs/2001.07305 (2020) - [i7]Nanzhe Wang, Haibin Chang, Dongxiao Zhang:
Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network. CoRR abs/2004.13560 (2020) - [i6]Nanzhe Wang, Haibin Chang, Dongxiao Zhang:
Deep-Learning based Inverse Modeling Approaches: A Subsurface Flow Example. CoRR abs/2007.15580 (2020) - [i5]Nanzhe Wang, Haibin Chang, Dongxiao Zhang:
Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling. CoRR abs/2011.08618 (2020)
2010 – 2019
- 2019
- [j3]Haibin Chang, Dongxiao Zhang:
Identification of physical processes via combined data-driven and data-assimilation methods. J. Comput. Phys. 393: 337-350 (2019) - [j2]Yuntian Chen, Haibin Chang, Jin Meng, Dongxiao Zhang:
Ensemble Neural Networks (ENN): A gradient-free stochastic method. Neural Networks 110: 170-185 (2019) - [i4]Yuntian Chen, Haibin Chang, Meng Jin, Dongxiao Zhang:
Ensemble Neural Networks (ENN): A gradient-free stochastic method. CoRR abs/1908.01113 (2019) - [i3]Hao Xu, Haibin Chang, Dongxiao Zhang:
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data. CoRR abs/1908.04463 (2019) - [i2]Nanzhe Wang, Dongxiao Zhang, Haibin Chang, Heng Li:
Deep Learning of Subsurface Flow via Theory-guided Neural Network. CoRR abs/1911.00103 (2019) - 2018
- [i1]Haibin Chang, Dongxiao Zhang:
Identification of physical processes via combined data-driven and data-assimilation methods. CoRR abs/1810.11977 (2018) - 2010
- [j1]Haibin Chang, Dongxiao Zhang, Zhiming Lu:
History matching of facies distribution with the EnKF and level set parameterization. J. Comput. Phys. 229(20): 8011-8030 (2010)
Coauthor Index
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