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ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 4
by another GNN model. In contrast to state‑of‑the‑art [6] Franco Scarselli, Marco Gori, Ah Chung Tsoi,
solutions based on costly optimization algorithms, the Markus Hagenbuchner, and Gabriele Monfardini.
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We tested NetXplain over RouteNet, a GNN model that [7] Justin Gilmer, Samuel S Schoenholz, Patrick F Riley,
predicts per‑source‑destination delays in computer net‑ Oriol Vinyals, and George E Dahl. “Neural message
works, and showed that our solution can produce an out‑ passing for quantum chemistry”. In: arXiv preprint
put equivalent to state‑of‑the‑art solutions with an exe‑ arXiv:1704.01212 (2017).
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[8] Peter Battaglia, Razvan Pascanu, Matthew Lai,
networks up to 24 nodes. Moreover, we discussed the
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potential applications that can have this GNN‑based ex‑
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such as those described in Section 7, as well as making Leskovec. “Modeling polypharmacy side ef‑
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ACKNOWLEDGEMENT works for web‑scale recommender systems”. In:
Proceedings of the ACM SIGKDD International Con‑
This work has been supported by the Spanish MINECO ference on Knowledge Discovery & Data Mining.
under contract TEC2017‑90034‑C2‑1‑R (ALLIANCE) and 2018, pp. 974–983.
the Catalan Institution for Research and Advanced Stud‑ [11] Wenqi Fan et al. “Graph neural networks for social
ies (ICREA). recommendation”. In: The ACM World Wide Web
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