Yihong Ma

According to our database, Yihong Ma authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks.

Yihong Ma, Ning Yan, Jiayu Li, Masood S. Mortazavi, Nitesh V. Chawla

Proceedings of the ACM on Web Conference 2024, 2024

Are we Making Much Progress? Revisiting Chemical Reaction Yield Prediction from an Imbalanced Regression Perspective.

Yihong Ma, Xiaobao Huang, Bozhao Nan, Nuno Moniz, Xiangliang Zhang, Olaf Wiest, Nitesh V. Chawla

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

2023

Modeling Co-Evolution of Attributed and Structural Information in Graph Sequence.

Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang

IEEE Trans. Knowl. Data Eng., 2023

Detecting Anomalies in Small Unmanned Aerial Systems via Graphical Normalizing Flows.

Yihong Ma, Md Nafee Al Islam, Jane Cleland-Huang, Nitesh V. Chawla

IEEE Intell. Syst., 2023

Class-Imbalanced Learning on Graphs: A Survey.

Yihong Ma, Yijun Tian, Nuno Moniz, Nitesh V. Chawla

CoRR, 2023

Graph-based Molecular Representation Learning.

Zhichun Guo, Kehan Guo, Bozhao Nan, Yijun Tian, Roshni G. Iyer, Yihong Ma, Olaf Wiest, Xiangliang Zhang, Wei Wang, Chuxu Zhang, Nitesh V. Chawla

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

RESAM: Requirements Elicitation and Specification for Deep-Learning Anomaly Models with Applications to UAV Flight Controllers.

Md Nafee Al Islam, Yihong Ma, Pedro Alarcon Granadeno, Nitesh V. Chawla, Jane Cleland-Huang

Proceedings of the 30th IEEE International Requirements Engineering Conference, 2022

Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks.

Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting.

Yihong Ma, Patrick Gérard, Yijun Tian, Zhichun Guo, Nitesh V. Chawla

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2020

Learning Attribute-Structure Co-Evolutions in Dynamic Graphs.

Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang

CoRR, 2020