2023[ to top ]
  • Power flow forecasts at transmission grid nodes using Graph Neural Networks. Beinert, Dominik; Holzhüter, Clara; Thomas, Josephine; Vogt, Stephan. In Energy and AI, 14(1), bl 100262. Elsevier, 2023.
  • Graph Neural Networks Designed for Different Graph Types: A Survey. Thomas, Josephine; Moallemy-Oureh, Alice; Beddar-Wiesing, Silvia; Holzhüter, Clara. In Transactions on Machine Learning Research. 2023.
2022[ to top ]
  • Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs. Beddar-Wiesing, Silvia; D’Inverno, Giuseppe Alessio; Graziani, Caterina; Lachi, Veronica; Moallemy-Oureh, Alice; Scarselli, Franco; Thomas, Josephine. In arXiv e-prints, bl arXiv:2210.03990. 2022.
2021[ to top ]
  • A Note on the Modeling Power of Different Graph Types. Thomas, Josephine M.; Beddar-Wiesing, Silvia; Moallemy-Oureh, Alice; Nather, Rüdiger. In arXiv e-prints, bl arXiv:2109.10708. 2021.
2017[ to top ]
  • Machine learning meets complex networks via coalescent embedding in the hyperbolic space. Muscoloni, Alessandro; Thomas, Josephine Maria; Ciucci, Sara; Bianconi, Ginestra; Cannistraci, Carlo Vittorio. In Nature Communications, 8(1), bl 1615. Springer, 2017.
2015[ to top ]
  • Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks. Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Cannistraci, Carlo Vittorio. In New Journal of Physics, 17(11), bl 113037. IOP Publishing, 2015.