| Frequency-domain mlps are more effective learners in time series forecasting K Yi, Q Zhang, W Fan, S Wang, P Wang, H He, N An, D Lian, L Cao, Z Niu Advances in Neural Information Processing Systems 36, 76656-76679, 2023 | 152 | 2023 |
| FourierGNN: Rethinking multivariate time series forecasting from a pure graph perspective K Yi, Q Zhang, W Fan, H He, L Hu, P Wang, N An, L Cao, Z Niu Advances in neural information processing systems 36, 69638-69660, 2023 | 106 | 2023 |
| Learning urban community structures: A collective embedding perspective with periodic spatial-temporal mobility graphs P Wang, Y Fu, J Zhang, X Li, D Lin ACM Transactions on Intelligent Systems and Technology (TIST) 9 (6), 1-28, 2018 | 87 | 2018 |
| Unifying inter-region autocorrelation and intra-region structures for spatial embedding via collective adversarial learning Y Zhang, Y Fu, P Wang, X Li, Y Zheng Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 84 | 2019 |
| You are how you drive: Peer and temporal-aware representation learning for driving behavior analysis P Wang, Y Fu, J Zhang, P Wang, Y Zheng, C Aggarwal Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 84 | 2018 |
| Incremental mobile user profiling: Reinforcement learning with spatial knowledge graph for modeling event streams P Wang, K Liu, L Jiang, X Li, Y Fu Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 83 | 2020 |
| Adversarial substructured representation learning for mobile user profiling P Wang, Y Fu, H Xiong, X Li Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 83 | 2019 |
| Dish-ts: a general paradigm for alleviating distribution shift in time series forecasting W Fan, P Wang, D Wang, D Wang, Y Zhou, Y Fu Proceedings of the AAAI conference on artificial intelligence 37 (6), 7522-7529, 2023 | 74 | 2023 |
| Job2Vec: Job title benchmarking with collective multi-view representation learning D Zhang, J Liu, H Zhu, Y Liu, L Wang, P Wang, H Xiong Proceedings of the 28th ACM International Conference on Information and …, 2019 | 63 | 2019 |
| Autofs: Automated feature selection via diversity-aware interactive reinforcement learning W Fan, K Liu, H Liu, P Wang, Y Ge, Y Fu 2020 IEEE International Conference on Data Mining (ICDM), 1008-1013, 2020 | 56 | 2020 |
| Efficient region embedding with multi-view spatial networks: A perspective of locality-constrained spatial autocorrelations Y Fu, P Wang, J Du, L Wu, X Li Proceedings of the AAAI conference on artificial intelligence 33 (01), 906-913, 2019 | 52 | 2019 |
| Jiadi Du, Le Wu, and Xiaolin Li. 2019. Efficient region embedding with multi-view spatial networks: A perspective of locality-constrained spatial autocorrelations Y Fu, P Wang Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 906-913, 2019 | 44 | 2019 |
| Ensemble-spotting: Ranking urban vibrancy via poi embedding with multi-view spatial graphs P Wang, J Zhang, G Liu, Y Fu, C Aggarwal Proceedings of the 2018 SIAM International Conference on Data Mining, 351-359, 2018 | 37 | 2018 |
| E-BERT: A phrase and product knowledge enhanced language model for e-commerce D Zhang, Z Yuan, Y Liu, F Zhuang, H Chen, H Xiong arXiv preprint arXiv:2009.02835, 2020 | 36 | 2020 |
| Reinforced imitative graph representation learning for mobile user profiling: An adversarial training perspective D Wang, P Wang, K Liu, Y Zhou, CE Hughes, Y Fu Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4410-4417, 2021 | 34 | 2021 |
| Reimagining city configuration: Automated urban planning via adversarial learning D Wang, Y Fu, P Wang, B Huang, CT Lu Proceedings of the 28th international conference on advances in geographic …, 2020 | 34 | 2020 |
| Spatiotemporal representation learning for driving behavior analysis: A joint perspective of peer and temporal dependencies P Wang, X Li, Y Zheng, C Aggarwal, Y Fu IEEE Transactions on Knowledge and Data Engineering 33 (2), 728-741, 2019 | 31 | 2019 |
| Representing urban forms: A collective learning model with heterogeneous human mobility data Y Fu, G Liu, Y Ge, P Wang, H Zhu, C Li, H Xiong IEEE transactions on knowledge and data engineering 31 (3), 535-548, 2018 | 30 | 2018 |
| Exploiting Mutual Information for Substructure-aware Graph Representation Learning P Wang, Y Fu, Y Zhou, K Liu, X Li, K Hua Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 28 | 2020 |
| A comprehensive survey on data augmentation Z Wang, P Wang, K Liu, P Wang, Y Fu, CT Lu, CC Aggarwal, J Pei, ... arXiv preprint arXiv:2405.09591, 2024 | 26 | 2024 |
Yanjie FuAssociate Professor, School of Computing and AI, Arizona State UniversityPotvrđena adresa e-pošte na asu.edu
