| A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems M Tang, Y Liu, LJ Durlofsky Journal of Computational Physics 413, 109456, 2020 | 237 | 2020 |
| Deep-learning-based surrogate flow modeling and geological parameterization for data assimilation in 3D subsurface flow M Tang, Y Liu, LJ Durlofsky Computer Methods in Applied Mechanics and Engineering 376, 113636, 2021 | 93 | 2021 |
| Towards a predictor for CO2 plume migration using deep neural networks G Wen, M Tang, SM Benson International Journal of Greenhouse Gas Control 105, 103223, 2021 | 70 | 2021 |
| Deep-learning-based coupled flow-geomechanics surrogate model for CO2 sequestration M Tang, X Ju, LJ Durlofsky International Journal of Greenhouse Gas Control 118, 103692, 2022 | 51 | 2022 |
| Deep reinforcement learning for generalizable field development optimization J He, M Tang, C Hu, S Tanaka, K Wang, XH Wen, Y Nasir SPE Journal 27 (01), 226-245, 2022 | 33 | 2022 |
| Learning compressed sentence representations for on-device text processing D Shen, P Cheng, D Sundararaman, X Zhang, Q Yang, M Tang, ... arXiv preprint arXiv:1906.08340, 2019 | 27 | 2019 |
| Multiphase flow prediction with deep neural networks G Wen, M Tang, SM Benson arXiv preprint arXiv:1910.09657, 2019 | 9 | 2019 |
| History matching complex 3D systems using deep-learning-based surrogate flow modeling and CNN-PCA geological parameterization M Tang, Y Liu, LJ Durlofsky SPE Reservoir Simulation Conference?, D011S008R003, 2021 | 7 | 2021 |
| Deep-learning-based 3D geological parameterization and flow prediction for history matching M Tang, Y Liu, L Durlofsky ECMOR XVII 2020 (1), 1-18, 2020 | 2 | 2020 |
| History matching production and displacement data using derivative-free optimization M Tang Master’s thesis, Stanford University, 2018 | 2 | 2018 |
| Deep-Learning-Based Surrogate Modeling of Flow and Coupled Flow-Geomechanics for Data Assimilation in Subsurface Systems M Tang Stanford University, 2021 | 1 | 2021 |
| Understand Amazon Deforestation using Neural Network C Liang, M Tang | 1 | 2017 |
