Haibin Chang

Publication Activity (10 Years)

Years Active: 2010-2022
Publications (10 Years): 16

Top Topics

Weakly Supervised

Partial Differential Equations

Top Venues

J. Comput. Phys.

Neural Networks

Publications

Nanzhe Wang, Haibin Chang, Xiangzhao Kong, Martin O. Saar, Dongxiao Zhang
Deep learning based closed-loop optimization of geothermal reservoir production. CoRR (2022)
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 (2022)
Nanzhe Wang, Qinzhuo Liao, Haibin Chang, Dongxiao Zhang
Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network. CoRR (2022)
Tianhao He, Haibin Chang, Dongxiao Zhang
Identification of Physical Processes and Unknown Parameters of 3D Groundwater Contaminant Problems via Theory-guided U-net. CoRR (2022)
Nanzhe Wang, Haibin Chang, Dongxiao Zhang
Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network. CoRR (2021)
Nanzhe Wang, Haibin Chang, Dongxiao Zhang
Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network. CoRR (2020)
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 (2020)
Nanzhe Wang, Haibin Chang, Dongxiao Zhang
Deep-Learning based Inverse Modeling Approaches: A Subsurface Flow Example. CoRR (2020)
Hao Xu, Haibin Chang, Dongxiao Zhang
DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm. CoRR (2020)
Nanzhe Wang, Haibin Chang, Dongxiao Zhang
Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling. CoRR (2020)
Yuntian Chen, Haibin Chang, Meng Jin, Dongxiao Zhang
Ensemble Neural Networks (ENN): A gradient-free stochastic method. CoRR (2019)
Haibin Chang, Dongxiao Zhang
Identification of physical processes via combined data-driven and data-assimilation methods. J. Comput. Phys. 393 (2019)
Nanzhe Wang, Dongxiao Zhang, Haibin Chang, Heng Li
Deep Learning of Subsurface Flow via Theory-guided Neural Network. CoRR (2019)
Hao Xu, Haibin Chang, Dongxiao Zhang
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data. CoRR (2019)
Yuntian Chen, Haibin Chang, Jin Meng, Dongxiao Zhang
Ensemble Neural Networks (ENN): A gradient-free stochastic method. Neural Networks 110 (2019)
Haibin Chang, Dongxiao Zhang
Identification of physical processes via combined data-driven and data-assimilation methods. CoRR (2018)
Haibin Chang, Dongxiao Zhang, Zhiming Lu
History matching of facies distribution with the EnKF and level set parameterization. J. Comput. Phys. 229 (20) (2010)