2023[ to top ]
  • Thomas, J., Moallemy-Oureh, A., Beddar-Wiesing, S., Holzhüter, C.: Graph Neural Networks Designed for Different Graph Types: A Survey Transactions on Machine Learning Research. (2023).
2022[ to top ]
  • Beddar-Wiesing, S., D’Inverno, G.A., Graziani, C., Lachi, V., Moallemy-Oureh, A., Scarselli, F., Thomas, J.: Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs arXiv e-prints. arXiv:2210.03990 (2022).
  • Moallemy-Oureh, A.: Student Research Abstract: Continuous-Time Generative Graph Neural Network for Attributed Dynamic Graphs In: ACM/SIGAPP Symposium on Applied Computing (SAC). bll 600–603. ACM (2022).
2021[ to top ]
  • Thomas, J.M., Beddar-Wiesing, S., Moallemy-Oureh, A., Nather, R.: A Note on the Modeling Power of Different Graph Types arXiv e-prints. arXiv:2109.10708 (2021).