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