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publications

Dynamic Stochastic Block Model with Scale-free Characteristic for Temporal Complex Networks

Published in International Conference on Database Systems for Advanced Applications (DASFAA), 2019

Recommended citation: Wu, X., Jiao, P., Wang, Y., Li, T., Wang, W., & Wang, B. (2019). "Dynamic Stochastic Block Model with Scale-free Characteristic for Temporal Complex Networks." International Conference on Database Systems for Advanced Applications, 502-518.
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Exploring the Transition Behavior of Nodes in Temporal Networks Based on Dynamic Community Detection

Published in Future Generation Computer Systems, 2020

Recommended citation: Li, T., Wang, W., Wu, X., Wu, H., Jiao, P., & Yu, Y. (2020). "Exploring the Transition Behavior of Nodes in Temporal Networks Based on Dynamic Community Detection." Future Generation Computer Systems, 107, 458-468.
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Generative evolutionary anomaly detection in dynamic networks

Published in IEEE Transactions on Knowledge and Data Engineering, 2021

Recommended citation: Jiao, P., Li, T., Xie, Y., Wang, Y., Wang, W., He, D., & Wu, H. (2021). "Generative evolutionary anomaly detection in dynamic networks." IEEE Transactions on Knowledge and Data Engineering, 35(12), 12234-12248.
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Lower Order Information Preserved Network Embedding Based on Non-negative Matrix Decomposition

Published in Information Sciences, 2021

Recommended citation: Tian, Q., Pan, L., Zhang, W., Li, T., Wu, H., Jiao, P., & Wang, W. (2021). "Lower Order Information Preserved Network Embedding Based on Non-negative Matrix Decomposition." Information Sciences, 572, 43-56.
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Exploring temporal community structure via network embedding

Published in IEEE Transactions on Cybernetics, 2022

Recommended citation: Li, T., Wang, W., Jiao, P., Wang, Y., Ding, R., Wu, H., Pan, L., & Jin, D. (2022). "Exploring temporal community structure via network embedding." IEEE Transactions on Cybernetics, 53(11), 7021-7033.
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HB-DSBM: Modeling the Dynamic Complex Networks from Community Level to Node Level

Published in IEEE Transactions on Neural Networks and Learning Systems, 2022

Recommended citation: Jiao, P., Li, T., Wu, H., Wang, C. D., He, D., & Wang, W. (2022). "HB-DSBM: Modeling the Dynamic Complex Networks from Community Level to Node Level." IEEE Transactions on Neural Networks and Learning Systems, 34(11), 8310-8323.
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Joint Community and Structural Hole Spanner Detection via Graph Contrastive Learning

Published in International Conference on Knowledge Science, Engineering and Management (KSEM), 2023

Recommended citation: Zhang, J., Wang, W., Li, T., Shao, M., Liu, J., & Sun, Y. (2023). "Joint Community and Structural Hole Spanner Detection via Graph Contrastive Learning." International Conference on Knowledge Science, Engineering and Management.
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Multi-view change point detection in dynamic networks

Published in Information Sciences, 2023

Recommended citation: Xie, Y., Wang, W., Shao, M., Li, T., & Yu, Y. (2023). "Multi-view change point detection in dynamic networks." Information Sciences, 629, 344-357.
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Robust Few-Shot Graph Anomaly Detection via Graph Coarsening

Published in International Conference on Knowledge Science, Engineering and Management (KSEM), 2023

Recommended citation: Li, L., Sun, Y., Li, T., & Shao, M. (2023). "Robust Few-Shot Graph Anomaly Detection via Graph Coarsening." International Conference on Knowledge Science, Engineering and Management.
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A Deep Contrastive Framework for Unsupervised Temporal Link Prediction in Dynamic Networks

Published in Information Sciences, 2024

Recommended citation: Jiao, P., Zhang, X., Liu, Z., Zhang, L., Wu, H., Gao, M., Li, T., & Wu, J. (2024). "A Deep Contrastive Framework for Unsupervised Temporal Link Prediction in Dynamic Networks." Information Sciences, 667, 120499.
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Informative Subgraphs Aware Masked Auto-encoder in Dynamic Graphs

Published in 2024 IEEE International Conference on Data Mining (ICDM), 2024

Recommended citation: Jiao, P., Zhang, X., Gao, M., Li, T., & Zhao, Z. (2024). "Informative Subgraphs Aware Masked Auto-encoder in Dynamic Graphs." 2024 IEEE International Conference on Data Mining (ICDM), 161-170.
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VGGM: Variational Graph Gaussian Mixture Model for Unsupervised Change Point Detection in Dynamic Networks

Published in IEEE Transactions on Information Forensics and Security, 2024

Recommended citation: Zhang, X., Jiao, P., Gao, M., Li, T., Wu, Y., Wu, H., & Zhao, Z. (2024). "VGGM: Variational Graph Gaussian Mixture Model for Unsupervised Change Point Detection in Dynamic Networks." IEEE Transactions on Information Forensics and Security, 19, 4272-4284.
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Counterfactual Learning for Higher-order Relation Prediction in Heterogeneous Information Networks

Published in Neural Networks, 2025

Recommended citation: Guo, X., Li, J., Jiao, P., Zhang, W., Li, T., & Wang, W. (2025). "Counterfactual Learning for Higher-order Relation Prediction in Heterogeneous Information Networks." Neural Networks, 183, 107024.
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DVGMAE: Self-Supervised Dynamic Variational Graph Masked Autoencoder

Published in IEEE Transactions on Neural Networks and Learning Systems, 2025

Recommended citation: Gao, M., Zhang, X., Jiao, P., Li, T., & Zhao, Z. (2025). "DVGMAE: Self-Supervised Dynamic Variational Graph Masked Autoencoder." IEEE Transactions on Neural Networks and Learning Systems.
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HSDP: Hypergraph and Structure-aware Representation Learning for Information Diffusion Prediction

Published in SSRN (Preprint), 2025

Recommended citation: Zhang, W., Wang, W., Guo, X., Li, T., & Shao, M. (2025). "HSDP: Hypergraph and Structure-aware Representation Learning for Information Diffusion Prediction." SSRN.
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Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning

Published in Proceedings of the AAAI Conference on Artificial Intelligence, 2026

Recommended citation: Zhang, X., Jiao, P., Gao, M., Li, T., & Guo, X. (2026). "Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning." Proceedings of the AAAI Conference on Artificial Intelligence, 40(19), 16379.
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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015