| Supervised descent learning technique for 2-D microwave imaging R Guo, X Song, M Li, F Yang, S Xu, A Abubakar IEEE Transactions on Antennas and Propagation 67 (5), 3550-3554, 2019 | 119 | 2019 |
| Machine learning in electromagnetics with applications to biomedical imaging: A review M Li, R Guo, K Zhang, Z Lin, F Yang, S Xu, X Chen, A Massa, A Abubakar IEEE Antennas and Propagation Magazine 63 (3), 39-51, 2021 | 66 | 2021 |
| Joint inversion of audio-magnetotelluric and seismic travel time data with deep learning constraint R Guo, HM Yao, M Li, MKP Ng, L Jiang, A Abubakar IEEE Transactions on Geoscience and Remote Sensing 59 (9), 7982-7995, 2020 | 55 | 2020 |
| Physics embedded deep neural network for solving full-wave inverse scattering problems R Guo, Z Lin, T Shan, X Song, M Li, F Yang, S Xu, A Abubakar IEEE transactions on antennas and propagation 70 (8), 6148-6159, 2021 | 52 | 2021 |
| A supervised descent learning technique for solving directional electromagnetic logging-while-drilling inverse problems Y Hu, R Guo, Y Jin, X Wu, M Li, A Abubakar, J Chen IEEE Transactions on Geoscience and Remote Sensing 58 (11), 8013-8025, 2020 | 51 | 2020 |
| Physics embedded deep neural network for solving volume integral equation: 2-D case R Guo, T Shan, X Song, M Li, F Yang, S Xu, A Abubakar IEEE Transactions on Antennas and Propagation 70 (8), 6135-6147, 2021 | 43 | 2021 |
| Pixel-and model-based microwave inversion with supervised descent method for dielectric targets R Guo, Z Jia, X Song, M Li, F Yang, S Xu, A Abubakar IEEE Transactions on Antennas and Propagation 68 (12), 8114-8126, 2020 | 43 | 2020 |
| Application of supervised descent method for 2D magnetotelluric data inversion R Guo, M Li, F Yang, S Xu, A Abubakar Geophysics 85 (4), WA53-WA65, 2020 | 42 | 2020 |
| Supervised descent learning for thoracic electrical impedance tomography K Zhang, R Guo, M Li, F Yang, S Xu, A Abubakar IEEE Transactions on Biomedical Engineering 68 (4), 1360-1369, 2020 | 39 | 2020 |
| Low-frequency data prediction with iterative learning for highly nonlinear inverse scattering problems Z Lin, R Guo, M Li, A Abubakar, T Zhao, F Yang, S Xu IEEE Transactions on Microwave Theory and Techniques 69 (10), 4366-4376, 2021 | 37 | 2021 |
| Application of supervised descent method to transient electromagnetic data inversion R Guo, M Li, G Fang, F Yang, S Xu, A Abubakar Geophysics 84 (4), E225-E237, 2019 | 34 | 2019 |
| Solving combined field integral equation with deep neural network for 2-D conducting object R Guo, Z Lin, T Shan, M Li, F Yang, S Xu, A Abubakar IEEE Antennas and Wireless Propagation Letters 20 (4), 538-542, 2021 | 25 | 2021 |
| Enhanced supervised descent learning technique for electromagnetic inverse scattering problems by the deep convolutional neural networks HM Yao, R Guo, M Li, L Jiang, MKP Ng IEEE Transactions on Antennas and Propagation 70 (8), 6195-6206, 2022 | 22 | 2022 |
| Neural network-based supervised descent method for 2D electrical impedance tomography Z Lin, R Guo, K Zhang, M Li, F Yang, S Xu, A Abubakar Physiological Measurement 41 (7), 074003, 2020 | 22 | 2020 |
| Physics-embedded machine learning for electromagnetic data imaging: Examining three types of data-driven imaging methods R Guo, T Huang, M Li, H Zhang, YC Eldar IEEE Signal Processing Magazine 40 (2), 18-31, 2023 | 21 | 2023 |
| Application of multitask learning for 2-D modeling of magnetotelluric surveys: TE case T Shan, R Guo, M Li, F Yang, S Xu, L Liang IEEE Transactions on Geoscience and Remote Sensing 60, 1-9, 2021 | 21 | 2021 |
| Physics-informed supervised residual learning for electromagnetic modeling T Shan, J Zeng, X Song, R Guo, M Li, F Yang, S Xu IEEE Transactions on Antennas and Propagation 71 (4), 3393-3407, 2023 | 19 | 2023 |
| First arrival traveltime tomography using supervised descent learning technique R Guo, M Li, F Yang, S Xu, A Abubakar Inverse Problems 35 (10), 105008, 2019 | 17 | 2019 |
| Spatial resolution matching of microwave radiometer data with convolutional neural network Y Li, W Hu, S Chen, W Zhang, R Guo, J He, L Ligthart Remote Sensing 11 (20), 2432, 2019 | 14 | 2019 |
| Application of supervised descent method for transient EM data inversion R Guo, M Li, F Yang, S Xu, G Fang, A Abubakar SEG Technical Program Expanded Abstracts 2018, 2126-2130, 2018 | 13 | 2018 |
