| Spatiotemporal data mining: A computational perspective S Shekhar, Z Jiang, RY Ali, E Eftelioglu, X Tang, VMV Gunturi, X Zhou ISPRS International Journal of Geo-Information 4 (4), 2306-2338, 2015 | 272 | 2015 |
| Monitoring land-cover changes: A machine-learning perspective A Karpatne, Z Jiang, RR Vatsavai, S Shekhar, V Kumar IEEE Geoscience and Remote Sensing Magazine 4 (2), 8-21, 2016 | 115 | 2016 |
| A survey on spatial prediction methods Z Jiang IEEE transactions on knowledge and Data Engineering 31 (9), 1645-1664, 2018 | 107 | 2018 |
| Spatial Big Data Science: Classification Techniques for Earth Observation Imagery Z Jiang, S Shekhar Springer, 2017 | 96* | 2017 |
| STDEN: Towards physics-guided neural networks for traffic flow prediction J Ji, J Wang, Z Jiang, J Jiang, H Zhang Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4048-4056, 2022 | 91 | 2022 |
| A neighborhood graph based approach to regional co-location pattern discovery: A summary of results P Mohan, S Shekhar, JA Shine, JP Rogers, Z Jiang, N Wayant Proceedings of the 19th ACM SIGSPATIAL international conference on advances …, 2011 | 86 | 2011 |
| Focal-test-based spatial decision tree learning Z Jiang, S Shekhar, X Zhou, J Knight, J Corcoran IEEE Transactions on Knowledge and Data Engineering 27 (6), 1547-1559, 2014 | 60 | 2014 |
| Visualizing traffic accident hotspots based on spatial-temporal network kernel density estimation B Romano, Z Jiang Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances …, 2017 | 51 | 2017 |
| A survey on uncertainty quantification methods for deep neural networks: An uncertainty source perspective W He, Z Jiang arXiv preprint arXiv:2302.13425, 2023 | 50 | 2023 |
| An attention U-Net model for detection of fine-scale hydrologic streamlines Z Xu, S Wang, LV Stanislawski, Z Jiang, N Jaroenchai, AM Sainju, ... Environmental Modelling & Software 140, 104992, 2021 | 50 | 2021 |
| Traffic flow prediction based on spatiotemporal potential energy fields J Wang, J Ji, Z Jiang, L Sun IEEE Transactions on Knowledge and Data Engineering 35 (9), 9073-9087, 2022 | 48 | 2022 |
| CurvaNet: Geometric deep learning based on directional curvature for 3D shape analysis W He, Z Jiang, C Zhang, AM Sainju Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 48 | 2020 |
| The nexus of food, energy, and water resources: Visions and challenges in spatial computing E Eftelioglu, Z Jiang, X Tang, S Shekhar Advances in Geocomputation: Geocomputation 2015--The 13th International …, 2017 | 48 | 2017 |
| Learning spatial decision tree for geographical classification: a summary of results Z Jiang, S Shekhar, P Mohan, J Knight, J Corcoran Proceedings of the 20th International Conference on Advances in Geographic …, 2012 | 46 | 2012 |
| Geographical hidden markov tree for flood extent mapping M Xie, Z Jiang, AM Sainju Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 35 | 2018 |
| Spatial ensemble learning for heterogeneous geographic data with class ambiguity Z Jiang, AM Sainju, Y Li, S Shekhar, J Knight ACM Transactions on Intelligent Systems and Technology (TIST) 10 (4), 1-25, 2019 | 33 | 2019 |
| Parallel grid-based colocation mining algorithms on GPUs for big spatial event data AM Sainju, D Aghajarian, Z Jiang, S Prasad IEEE Transactions on Big Data 6 (1), 107-118, 2018 | 33 | 2018 |
| Spatial computing perspective on food energy and water nexus E Eftelioglu, Z Jiang, R Ali, S Shekhar Journal of Environmental Studies and Sciences 6, 62-76, 2016 | 33 | 2016 |
| Interpretable spatiotemporal deep learning model for traffic flow prediction based on potential energy fields J Ji, J Wang, Z Jiang, J Ma, H Zhang 2020 IEEE international conference on data mining (ICDM), 1076-1081, 2020 | 32 | 2020 |
| Fairness by “where”: A statistically-robust and model-agnostic bi-level learning framework Y Xie, E He, X Jia, W Chen, S Skakun, H Bao, Z Jiang, R Ghosh, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12208 …, 2022 | 31 | 2022 |
