Xiong, D., Li, X., Song, E., et al. (2025). WTAN: Wavelet Transform-based Attention Network for Tail Strike Prediction and Interpretable Analysis.(Submitted)
Liao, L., Zheng, L., Shang, J., Li, X., Zhong, J., & Wei, K.. (2025). Query-Guided Temporal Confidence Network for Noisy Temporal Knowledge Graph Reasoning.(Submitted)
Zhang, H., Sun, H., Liu, Y., Zhao, X., Li, X., Shang, J., Zheng, L.. (2025). CCAN: Channel-wise Clustering and Attention Networks for Interpretable Hard Landing Prediction.(Submitted)
Cai, J., Shang, J., Li, X., Li, C., & Zheng, L. (2025). Fine-Grained Time and Hidden Feature Learning for Interpretable Hard Landing Prediction Based on QAR Data. IEEE Transactions on Intelligent Transportation Systems.
* (2025). Crossperformer: Cross-period Transformer for Time Series Forecasting. (Submitted)
* (2025). Causal Mamba for Multivariate Time Series Forecasting. (Submitted)
Li, C., Li, X., Zheng, L., Shang, J., et al. (2025). MVAN: Towards Interpretable Joint Prediction of Multiple Flight Safety Events with Multi-View Attention Network.(Submitted)
Shang, J., Li, X., Zhang, R., Zheng, L., Li, X., Zhang, R., ... & Sun, H. (2025). A Dual Two-Stage Attention-based Model for interpretable hard landing prediction from flight data. Engineering Applications of Artificial Intelligence, 154, 110911.
Yan, W., Li, X., Zhao, X., et al. (2025). MGAN: Multi-scale Graph Attention Network for Flight Safety Incidents Detection.(Submitted)
Song, L., Sun, H., Li, X., et al. (2025). IATCN: Interpretable Attention-Enhanced Temporal Convolutional Network for Multiple Flight Safety Incidents Prediction.(Submitted)
Yan, W., Li, X., Zheng, L., Shang, J., Wu, L., Liu, H., ... & Qian, Y. (2025). DGAN: Flight data anomaly detection based on dual-view graph attention network. IEEE Sensors Journal.
Huang, Y., Shang, J., Li, X., et al. (2025). MultiSafe: Multiple Flight Safety Events Prediction Based on Interpretable Deep Multi-Task Learning.(Submitted)
Liao, L., Zheng, L., Chen, F., Shang, J., Li, X., & Li, W. (2025). ERD-Net: Modeling entity and relation dynamics for Temporal Knowledge Graph reasoning. Knowledge-Based Systems, 317, 113404.
Song, L., Li, X., Liu, H., Wu, L., Sun, H., Zheng, L., & Shang, J. (2025). MDGNN: Multiple Flight Safety Incidents Prediction Model Based on Dynamic Graph Neural Networks. IEEE Transactions on Intelligent Transportation Systems.
Li, X., Zheng, L., Shang, J., Liao, L., Zhang, J., & Zhong, J. (2025). MRI: Memory Retention Mechanism for Interpretable Time Series Forecasting. IEEE Transactions on Pattern Analysis and Machine Intelligence.(Submitted)
Han, Y., Shang, J., Li, R., Li, X., Liao, L., Zheng, L., & Min, G.. (2025). Boosting Low-budget Active Learning with Label Calibration and Unsupervised Representations. IEEE Transactions on Pattern Analysis and Machine Intelligence. (Submitted)
* (2025). Context-Aware Learning and Pattern Decomposition for Temporal Knowledge Graph Reasoning.(Submitted)
Li, C., Li, X., Chen, H., Zheng, L., Sun, H., Shang, J. (2024). DUVET: Dual View Enhanced Transformer for MultivariateFlight Time series Anomaly Detection.
Liao, L., Zheng, L., Shang, J., Li, X., & Chen, F. (2024). ATPF: An Adaptive Temporal Perturbation Framework for Adversarial Attacks on Temporal Knowledge Graph. IEEE Transactions on Knowledge and Data Engineering.
Liu, Y., Wu, X., Tang, Y., Li, X., Sun, D., & Zheng, L. (2024). Decomposition with feature attention and graph convolution network for traffic forecasting. Knowledge-Based Systems, 112193.
Li, X., Shang, J., Zheng, L., Wang, Q., Liu, D., Liu, X., ... & Sun, H. (2024). IMTCN: An Interpretable Flight Safety Analysis and Prediction Model Based on Multi-Scale Temporal Convolutional Networks. IEEE Transactions on Intelligent Transportation Systems.
Chen, H., Shang, J., Zheng, L., Li, X., Liu, X., Sun, H., ... & Yu, L. (2023). SDTAN: Scalable Deep Time-Aware Attention Network for Interpretable Hard Landing Prediction. IEEE Transactions on Intelligent Transportation Systems, 24(9), 10211-10223.
Ma, J., Li, J., Li, X., & Li, X. (2021). PathSAGE: Spatial Graph Attention Neural Networks with Random Path Sampling. In Neural Information Processing: 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8–12, 2021, Proceedings, Part II 28 (pp. 111-120). Springer International Publishing.
Li, X., Shang, J., Zheng, L., Wang, Q., Sun, H., & Qi, L. (2021). Curvecluster+: Curve clustering for hard landing pattern recognition and risk evaluation based on flight data. IEEE Transactions on Intelligent Transportation Systems, 23(8), 12811-12821.
Yang, Y., Li, X., & Li, X. (2021, July). A relation-guided attention mechanism for relational triple extraction. In 2021 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.
Li, X., Wu, G., Zhou, S., Lin, X., & Li, X. (2022). Active instance segmentation with fractional-order network and reinforcement learning. The Visual Computer, 1-14.
Chen, H., Shang, J., Zhao, X., Li, X., Zheng, L., & Chen, F. (2020, October). A deep learning method for landing pitch prediction based on flight data. In 2020 IEEE 2nd International Conference on Civil Aviation Safety and Information Technology (ICCASIT (pp. 199-204). IEEE.
Li, X., Shang, J., Zheng, L., Liu, D., Qi, L., & Liu, L. (2019, August). CurveCluster: Automated recognition of hard landing patterns based on QAR curve clustering. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 602-609). IEEE.