Deep learning for graphs
Bacciu D, Bianchi FM, Paaßen B, Alippi C (2021)
In: {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}. Verleysen M (Ed); 89–98.
Konferenzbeitrag | Englisch
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Autor*in
Bacciu, Davide;
Bianchi, Filippo Maria;
Paaßen, BenjaminUniBi 
;
Alippi, Cesare
;
Alippi, CesareHerausgeber*in
Verleysen, Michel
Einrichtung
Abstract / Bemerkung
Deep learning for graphs encompasses all those neural models endowed with multiple layers of computation operating on data represented as graphs. The most common building blocks of these models are graph encoding layers, which compute a vector embedding for each node in a graph using message-passing operators. In this paper, we provide an overview of the key concepts in the field, point towards open questions, and frame the contributions of the ESANN 2021 special session into the broader context of deep learning for graphs
Erscheinungsjahr
2021
Titel des Konferenzbandes
{Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}
Seite(n)
89–98
Konferenz
Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Konferenzort
virtual
Konferenzdatum
2021-10-06 – 2021-10-08
Page URI
https://pub.uni-bielefeld.de/record/2978996
Zitieren
Bacciu D, Bianchi FM, Paaßen B, Alippi C. Deep learning for graphs. In: Verleysen M, ed. {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}. 2021: 89–98.
Bacciu, D., Bianchi, F. M., Paaßen, B., & Alippi, C. (2021). Deep learning for graphs. In M. Verleysen (Ed.), {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)} (p. 89–98).
Bacciu, Davide, Bianchi, Filippo Maria, Paaßen, Benjamin, and Alippi, Cesare. 2021. “Deep learning for graphs”. In {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}, ed. Michel Verleysen, 89–98.
Bacciu, D., Bianchi, F. M., Paaßen, B., and Alippi, C. (2021). “Deep learning for graphs” in {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}, Verleysen, M. ed. 89–98.
Bacciu, D., et al., 2021. Deep learning for graphs. In M. Verleysen, ed. {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}. pp. 89–98.
D. Bacciu, et al., “Deep learning for graphs”, {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}, M. Verleysen, ed., 2021, pp.89–98.
Bacciu, D., Bianchi, F.M., Paaßen, B., Alippi, C.: Deep learning for graphs. In: Verleysen, M. (ed.) {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}. p. 89–98. (2021).
Bacciu, Davide, Bianchi, Filippo Maria, Paaßen, Benjamin, and Alippi, Cesare. “Deep learning for graphs”. {Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021)}. Ed. Michel Verleysen. 2021. 89–98.
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