Recommender Systems (6 papers)
C. Gao, Y. Zheng, N. Li, Y. Li, Y. Qin, J. Piao, Y. Quan, J. Chang, D. Jin, X. He, Y. Li, "A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions", ACM Transactions on Recommender Systems, Volume 1,Issue 1, pages 1-51, March 2023.
Z. Yang, Z. Kuang, L. Yang, Q. Zhang, "A Recommendation Prediction Method based on the Estimation of PSD of Sampled Signals on Graph", Expert Systems with Applications, 2022.
H. Wang, M. Zhao, X. Xie, W. Li, M. Guo, “Knowledge Graph Convolutional Networks for Recommender Systems", ACM World Wild Web Conference, WWW 2019, pages 3307-3313, 2019.
H. Wang, F. Zhang, M. Zhang, J. Leskovec, M. Zhao, W. Li, Z. Wang, “Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems", ACM International Conference on Knowledge Discovery and Data Mining, SIGKDD 2019, pages 968-977, 2019.
X. Wang, X. He, Y. Cao, M. Liu, T. Chua, “KGAT: Knowledge Graph Attention Network for Recommendation", ACM International Conference on Knowledge Discovery and Data Mining, SIGKDD 2019, pages 950–958, 2019.
R. Ying, R. He, K. Chen, P. Eksombatchai, W. Hamilton, J. Leskovec, "Graph convolutional neural networks for web-scale recommender systems", ACM International Conference on Knowledge Discovery and Data Mining, SIGKDD 2018, pages 974-983, 2018.
Computers Networks (1 paper)
F. Geyer, S. Bondorf, "DeepTMA: Predicting Effective Contention Models for Network Calculus using Graph Neural Networks", IEEE INFOCOM IEEE Conference on Computer Communications, pages 1009-1017, 2019.