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FastGAE: Scalable graph autoencoders with stochastic subgraph decoding., , , , and . Neural Networks, (2021)FastGAE: Fast, Scalable and Effective Graph Autoencoders with Stochastic Subgraph Decoding., , , , and . CoRR, (2020)Muzeeglot : annotation multilingue et multi-sources d'entités musicales à partir de représentations de genres musicaux (Muzeeglot : cross-lingual multi-source music item annotation from music genre embeddings)., , , , and . JEP-TALN-RECITAL (Demos), page 18-21. ATALA et AFCP, (2020)Simple and Effective Graph Autoencoders with One-Hop Linear Models., , and . ECML/PKDD (1), volume 12457 of Lecture Notes in Computer Science, page 319-334. Springer, (2020)Adaptive Submodular Influence Maximization with Myopic Feedback., , and . CoRR, (2017)A Degeneracy Framework for Scalable Graph Autoencoders., , , and . IJCAI, page 3353-3359. ijcai.org, (2019)Carousel Personalization in Music Streaming Apps with Contextual Bandits., , and . RecSys, page 420-425. ACM, (2020)Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks., , and . CoRR, (2019)Contributions to Representation Learning with Graph Autoencoders and Applications to Music Recommendation. (Contributions à l'apprentissage de représentations à partir d'autoencodeurs de graphes et applications à la recommandation musicale).. Polytechnic Institute of Paris, Palaiseau, France, (2022)Adaptive Submodular Influence Maximization with Myopic Feedback., , and . ASONAM, page 455-462. IEEE Computer Society, (2018)