| Estimation of rapidly time-varying sparse channels W Li, JC Preisig IEEE Journal of Oceanic Engineering 32 (4), 927-939, 2008 | 586 | 2008 |
| Seismic facies classification using supervised convolutional neural networks and semisupervised generative adversarial networks M Liu, M Jervis, W Li, P Nivlet Geophysics 85 (4), O47-O58, 2020 | 131 | 2020 |
| Granger Causality for Time-Series Anomaly Detection YL Huida Qiu, NA Subrahmanya, W Li 2012 IEEE 12th International Conference on Data Mining, 1074-1079, 2012 | 114 | 2012 |
| PatentMiner: topic-driven patent analysis and mining J Tang, B Wang, Y Yang, P Hu, Y Zhao, X Yan, B Gao, M Huang, P Xu, ... Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 108 | 2012 |
| Focus detection from digital in-line holograms based on spectral norms W Li, NC Loomis, Q Hu, CS Davis Journal of the Optical Society of America A 24 (10), 3054-3062, 2007 | 103 | 2007 |
| Computational reconstruction of images from holograms JH Milgram, W Li Applied optics 41 (5), 853-864, 2002 | 88 | 2002 |
| Decentralized Fault Detection and Diagnosis via Sparse PCA based Decomposition and Maximum Entropy Decision Fusion M Grbovic, W Li, P Xu, AK Usadi, L Song, S Vucetic Journal of Process Control 22, 738-750, 2012 | 84 | 2012 |
| Systems and Methods for Event Detection and Diagnosis W LI, T O'CONNOR, S DASH, J SOMMERS WO Patent WO 2,015,099,964, 2015 | 82 | 2015 |
| Physics-driven deep-learning inversion with application to transient electromagnetics D Colombo, E Turkoglu, W Li, E Sandoval-Curiel, D Rovetta Geophysics 86 (3), E209-E224, 2021 | 79 | 2021 |
| Cold Start Approach for Data-Driven Fault Detection M Grbovic, W Li, NA Subrahmanya, AK Usadi, S Vucetic Industrial Informatics, IEEE Transactions on 9 (4), 2264-2273, 2013 | 47 | 2013 |
| Deep-learning electromagnetic monitoring coupled to fluid flow simulators D Colombo, W Li, E Sandoval-Curiel, GW McNeice Geophysics 85 (4), WA1-WA12, 2020 | 42 | 2020 |
| Classifying geological structure elements from seismic images using deep learning W Li SEG International Exposition and Annual Meeting, SEG-2018-2998036, 2018 | 41 | 2018 |
| Physics-constrained deep learning for ground roll attenuation N Pham, W Li Geophysics 87 (1), V15-V27, 2022 | 39 | 2022 |
| Statistical root cause analysis of novel faults based on digraph models Y Wan, F Yang, N Lv, H Xu, H Ye, W Li, P Xu, L Song, AK Usadi Chemical Engineering Research and Design 91 (1), 87-99, 2013 | 39 | 2013 |
| Machine learning in petrophysics: Advantages and limitations C Xu, L Fu, T Lin, W Li, S Ma Artificial Intelligence in Geosciences 3, 157-161, 2022 | 34 | 2022 |
| Sparse Reinforcement Learning via Convex Optimization Z Qin, W Li International Conference on Machine Learning (ICML), June 2014, 424-432, 2014 | 34 | 2014 |
| Synthetic sonic log generation with machine learning: A contest summary from five methods Y Yu, C Xu, S Misra, W Li, M Ashby, W Pan, T Deng, H Jo, JE Santos, L Fu, ... Petrophysics 62 (04), 393-406, 2021 | 33 | 2021 |
| Generating breakpoint-based timeline overview for news topic retrospection P Hu, M Huang, P Xu, W Li, AK Usadi, X Zhu 2011 IEEE 11th International Conference on Data Mining, 260-269, 2011 | 32 | 2011 |
| Finding nuggets in IP portfolios: core patent mining through textual temporal analysis P Hu, M Huang, P Xu, W Li, AK Usadi, X Zhu Proceedings of the 21st ACM international conference on Information and …, 2012 | 30 | 2012 |
| 3D seismic facies classification using convolutional neural network and semi-supervised generative adversarial network M Liu, W Li, M Jervis, P Nivlet SEG Technical Program Expanded Abstracts 2019, 4995-4999, 2019 | 28 | 2019 |
James PreisigPresident, JPAnalytics在 jpanalytics.com 的電子郵件地址已通過驗證
