| Link prediction in complex networks: a mutual information perspective F Tan, Y Xia, B Zhu PloS one 9 (9), e107056, 2014 | 163 | 2014 |
| Cascading failures of loads in interconnected networks under intentional attack F Tan, Y Xia, W Zhang, X Jin Europhysics Letters 102 (2), 28009, 2013 | 154 | 2013 |
| Distinct microbiological signatures associated with triple negative breast cancer S Banerjee, Z Wei, F Tan, KN Peck, N Shih, M Feldman, TR Rebbeck, ... Scientific reports 5 (1), 15162, 2015 | 119 | 2015 |
| Traffic congestion in interconnected complex networks F Tan, J Wu, Y Xia, CK Tse Physical Review E 89 (6), 062813, 2014 | 104 | 2014 |
| Robust-yet-fragile nature of interdependent networks F Tan, Y Xia, Z Wei Physical Review E 91 (5), 052809, 2015 | 62 | 2015 |
| Hybrid routing on scale-free networks F Tan, Y Xia Physica A: Statistical Mechanics and its Applications 392 (18), 4146-4153, 2013 | 57 | 2013 |
| Success Prediction on Crowdfunding with Multimodal Deep Learning C Cheng, F Tan, X Hou, Z Wei Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 52 | 2019 |
| A deep learning approach to competing risks representation in peer-to-peer lending F Tan, X Hou, J Zhang, Z Wei, Z Yan IEEE transactions on neural networks and learning systems 30 (5), 1565-1574, 2018 | 52 | 2018 |
| HABERTOR: An efficient and effective deep hatespeech detector T Tran, Y Hu, C Hu, K Yen, F Tan, K Lee, S Park arXiv preprint arXiv:2010.08865, 2020 | 36 | 2020 |
| Repulsive attention: Rethinking multi-head attention as bayesian inference B An, J Lyu, Z Wang, C Li, C Hu, F Tan, R Zhang, Y Hu, C Chen arXiv preprint arXiv:2009.09364, 2020 | 31 | 2020 |
| Tnt: Text normalization based pre-training of transformers for content moderation F Tan, Y Hu, C Hu, K Li, K Yen Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 22 | 2020 |
| A blended deep learning approach for predicting user intended actions F Tan, Z Wei, J He, X Wu, B Peng, H Liu, Z Yan 2018 IEEE international conference on data mining (ICDM), 487-496, 2018 | 22 | 2018 |
| What Makes Pre-trained Language Models Better Zero-shot Learners? J Lu, D Zhu, W Han, R Zhao, B Mac Namee, F Tan arXiv preprint arXiv:2209.15206, 2022 | 21 | 2022 |
| Time-aware latent hierarchical model for predicting house prices F Tan, C Cheng, Z Wei 2017 IEEE International Conference on Data Mining (ICDM), 1111-1116, 2017 | 16 | 2017 |
| Punifiedner: A prompting-based unified ner system for diverse datasets J Lu, R Zhao, B Mac Namee, F Tan Proceedings of the AAAI Conference on Artificial Intelligence 37 (11), 13327 …, 2023 | 15 | 2023 |
| Deeply coupled cross-modal prompt learning X Liu, W Tang, J Lu, R Zhao, Z Guo, F Tan Findings of the Association for Computational Linguistics: ACL 2023, 7957-7970, 2023 | 14 | 2023 |
| Elucidation of DNA methylation on N6-adenine with deep learning F Tan, T Tian, X Hou, X Yu, L Gu, F Mafra, BD Gregory, Z Wei, ... Nature Machine Intelligence 2 (8), 466-475, 2020 | 13 | 2020 |
| Modeling real estate for school district identification F Tan, C Cheng, Z Wei 2016 IEEE 16th International Conference on Data Mining (ICDM), 1227-1232, 2016 | 11 | 2016 |
| What Large Language Models Bring to Text-rich VQA? X Liu, W Tang, X Ni, J Lu, R Zhao, Z Li, F Tan arXiv preprint arXiv:2311.07306, 2023 | 9 | 2023 |
| Modeling and elucidation of housing price F Tan, C Cheng, Z Wei Data Mining and Knowledge Discovery, 1-27, 2019 | 9 | 2019 |
Zhi WeiProf of Comp Sci and Statistics, NJIT; Adjunct Prof. at UPenn.Verified email at njit.edu
