| Multi-level recommendation reasoning over knowledge graphs with reinforcement learning X Wang, K Liu, D Wang, L Wu, Y Fu, X Xie Proceedings of the ACM Web Conference 2022, 2098-2108, 2022 | 110 | 2022 |
| DeepSTCL: A deep spatio-temporal ConvLSTM for travel demand prediction D Wang, Y Yang, S Ning 2018 international joint conference on neural networks (IJCNN), 1-8, 2018 | 107 | 2018 |
| 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 | 69 | 2023 |
| Towards Automated Urban Planning: When Generative and ChatGPT-like AI Meets Urban Planning D Wang, CT Lu, Y Fu TSAS submited, 2023 | 48 | 2023 |
| Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective D Wang, P Wang, K Liu, Y Zhou, C Hughes, Y Fu AAAI 2021, 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 |
| Incremental causal graph learning for online root cause analysis D Wang, Z Chen, Y Fu, Y Liu, H Chen Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 28 | 2023 |
| Interdependent causal networks for root cause localization D Wang, Z Chen, J Ni, L Tong, Z Wang, Y Fu, H Chen Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 24 | 2023 |
| Reinforced explainable knowledge concept recommendation in MOOCs L Jiang, K Liu, Y Wang, D Wang, P Wang, Y Fu, M Yin ACM Transactions on Intelligent Systems and Technology 14 (3), 1-20, 2023 | 22 | 2023 |
| Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction D Wang, Y Fu, K Liu, X Li, Y Solihin KDD 2022, 2022 | 22 | 2022 |
| RATT: AThought Structure for Coherent and Correct LLMReasoning J Zhang, X Wang, W Ren, L Jiang, D Wang, K Liu arXiv preprint arXiv:2406.02746, 2024 | 21 | 2024 |
| C2IMUFS: Complementary and Consensus Learning-Based Incomplete Multi-View Unsupervised Feature Selection Y Huang, Z Shen, Y Cai, X Yi, D Wang, F Lv, T Li IEEE Transactions on Knowledge and Data Engineering 35 (10), 10681-10694, 2023 | 21 | 2023 |
| Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization D Wang, Z Chen, J Ni, L Tong, Z Wang, Y Fu, H Chen KDD 2023 Accepted, 2023 | 21 | 2023 |
| Automated Urban Planning for Reimagining City Configuration via Adversarial Learning: Quantification, Generation, and Evaluation D Wang, Y Fu, K Liu, F Chen, P Wang, CT Lu TSAS Accepted, 2021 | 20 | 2021 |
| Traceable Automatic Feature Transformation via Cascading Actor-Critic Agents M Xiao, D Wang, M Wu, Z Qiao, P Wang, K Liu, Y Zhou, Y Fu SDM 2023, 2022 | 19 | 2022 |
| Measuring urban vibrancy of residential communities using big crowdsourced geotagged data P Wang, K Liu, D Wang, Y Fu Frontiers in big Data 4, 690970, 2021 | 19 | 2021 |
| Beyond discrete selection: Continuous embedding space optimization for generative feature selection M Xiao, D Wang, M Wu, P Wang, Y Zhou, Y Fu 2023 IEEE International Conference on Data Mining (ICDM), 688-697, 2023 | 18 | 2023 |
| Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection D Wang, P Wang, J Zhou, L Sun, B Du, Y Fu ICDM 2020, 2020 | 18 | 2020 |
| Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy K Liu, P Wang, D Wang, W Du, DO Wu, Y Fu ICDM 2021, 2021 | 17 | 2021 |
| Traceable group-wise self-optimizing feature transformation learning: A dual optimization perspective M Xiao, D Wang, M Wu, K Liu, H Xiong, Y Zhou, Y Fu ACM Transactions on Knowledge Discovery from Data 18 (4), 1-22, 2024 | 16 | 2024 |
Yanjie FuAssociate Professor, School of Computing and AI, Arizona State UniversityVerified email at asu.edu