Haibin Chang - RankMe

18 papers Journal 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Analysis of influencing factors on teachers' AI literacy under the SOR framework: An empirical study based on PLS-SEM and fsQCA. Educ. Inf. Technol. Yimin Ning, Hanyi Zheng, Hongde Wu, Zhijie Jin, Haibin Chang, Tommy Tanu Wijaya
2022	J	`jnl`	Deep learning based closed-loop optimization of geothermal reservoir production. CoRR Nanzhe Wang, Haibin Chang, Xiangzhao Kong, Martin O. Saar, Dongxiao Zhang
2022	J	`jnl`	Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network. CoRR Nanzhe Wang, Qinzhuo Liao, Haibin Chang, Dongxiao Zhang
2022	J	`jnl`	Identification of Physical Processes and Unknown Parameters of 3D Groundwater Contaminant Problems via Theory-guided U-net. CoRR Tianhao He, Haibin Chang, Dongxiao Zhang
2022	J	`jnl`	Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network. J. Comput. Phys. Nanzhe Wang, Haibin Chang, Dongxiao Zhang
2021	J	`jnl`	Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network. CoRR Nanzhe Wang, Haibin Chang, Dongxiao Zhang
2020	J	`jnl`	DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm. CoRR Hao Xu, Haibin Chang, Dongxiao Zhang
2020	J	`jnl`	DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm. J. Comput. Phys. Hao Xu, Haibin Chang, Dongxiao Zhang
2020	J	`jnl`	Deep-Learning based Inverse Modeling Approaches: A Subsurface Flow Example. CoRR Nanzhe Wang, Haibin Chang, Dongxiao Zhang
2020	J	`jnl`	Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network. CoRR Nanzhe Wang, Haibin Chang, Dongxiao Zhang
2020	J	`jnl`	Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling. CoRR Nanzhe Wang, Haibin Chang, Dongxiao Zhang
2019	J	`jnl`	DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data. CoRR Hao Xu, Haibin Chang, Dongxiao Zhang
2019	J	`jnl`	Deep Learning of Subsurface Flow via Theory-guided Neural Network. CoRR Nanzhe Wang, Dongxiao Zhang, Haibin Chang, Heng Li
2019	J	`jnl`	Ensemble Neural Networks (ENN): A gradient-free stochastic method. CoRR Yuntian Chen, Haibin Chang, Meng Jin, Dongxiao Zhang
2019	J	`jnl`	Ensemble Neural Networks (ENN): A gradient-free stochastic method. Neural Networks Yuntian Chen, Haibin Chang, Jin Meng, Dongxiao Zhang
2019	J	`jnl`	Identification of physical processes via combined data-driven and data-assimilation methods. J. Comput. Phys. Haibin Chang, Dongxiao Zhang
2018	J	`jnl`	Identification of physical processes via combined data-driven and data-assimilation methods. CoRR Haibin Chang, Dongxiao Zhang
2010	J	`jnl`	History matching of facies distribution with the EnKF and level set parameterization. J. Comput. Phys. Haibin Chang, Dongxiao Zhang, Zhiming Lu

Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, Christoph Endres, Thorsten Holz, Mario Fritz