HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks.
Proceedings of the ACM on Web Conference 2024, 2024
Are we Making Much Progress? Revisiting Chemical Reaction Yield Prediction from an Imbalanced Regression Perspective.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024
Modeling Co-Evolution of Attributed and Structural Information in Graph Sequence.
IEEE Trans. Knowl. Data Eng., 2023
Detecting Anomalies in Small Unmanned Aerial Systems via Graphical Normalizing Flows.
IEEE Intell. Syst., 2023
Class-Imbalanced Learning on Graphs: A Survey.
CoRR, 2023
Graph-based Molecular Representation Learning.
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Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
RESAM: Requirements Elicitation and Specification for Deep-Learning Anomaly Models with Applications to UAV Flight Controllers.
Proceedings of the 30th IEEE International Requirements Engineering Conference, 2022
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Learning Attribute-Structure Co-Evolutions in Dynamic Graphs.
CoRR, 2020
A Study of Person Entity Extraction and Profiling from Classical Chinese Historiography.
Proceedings of the 2nd International Workshop on EntitY REtrieval co-located with 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), 2019