Le Yu

Orcid: 0000-0002-4908-3199

Affiliations:
  • Beihang University, SKLSDE Lab and BDBC, School of Computer Science and Engineering, Beijing, China


According to our database1, Le Yu authored at least 20 papers between 2019 and 2024.

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Timeline

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Bibliography

2024
Event-Based Dynamic Graph Representation Learning for Patent Application Trend Prediction.
IEEE Trans. Knowl. Data Eng., May, 2024

Continuous-Time User Preference Modelling for Temporal Sets Prediction.
IEEE Trans. Knowl. Data Eng., April, 2024

Multi-mode Spatial-Temporal Data Modeling with Fully Connected Networks.
Proceedings of the Knowledge Science, Engineering and Management, 2024

2023
Label-Enhanced Graph Neural Network for Semi-Supervised Node Classification.
IEEE Trans. Knowl. Data Eng., November, 2023

Heterogeneous Graph Representation Learning With Relation Awareness.
IEEE Trans. Knowl. Data Eng., June, 2023

A Simple Framework for Multi-mode Spatial-Temporal Data Modeling.
CoRR, 2023

Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification.
CoRR, 2023

Towards Better Dynamic Graph Learning: New Architecture and Unified Library.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Continuous-Time Graph Learning for Cascade Popularity Prediction.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Pretraining Language Models with Text-Attributed Heterogeneous Graphs.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Predicting Temporal Sets with Simplified Fully Connected Networks.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Adaptive Spatio-temporal Graph Neural Network for traffic forecasting.
Knowl. Based Syst., 2022

Modelling Evolutionary and Stationary User Preferences for Temporal Sets Prediction.
CoRR, 2022

Element-guided Temporal Graph Representation Learning for Temporal Sets Prediction.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

2021
Deep Heterogeneous Network for Temporal Set Prediction.
Knowl. Based Syst., 2021

Deep spatio-temporal graph convolutional network for traffic accident prediction.
Neurocomputing, 2021

Modelling the epidemic dynamics of COVID-19 with consideration of human mobility.
Int. J. Data Sci. Anal., 2021

2020
Hybrid Micro/Macro Level Convolution for Heterogeneous Graph Learning.
CoRR, 2020

Predicting Temporal Sets with Deep Neural Networks.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019
Traffic Accident Prediction Based on Deep Spatio-Temporal Analysis.
Proceedings of the 2019 IEEE SmartWorld, 2019


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