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Symmetric spaces for graph embeddings: a Finsler-Riemannian approach

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Learning faithful graph representations as sets of vertex embeddings has become a fundamental intermediary step in a wide range of machine learning applications. We propose the systematic use of symmetric spaces in representation learning, a class encompassing many of the previously used embedding t...

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Main Authors: López, Federico (Author) , Pozzetti, Maria Beatrice (Author) , Trettel, Steve (Author) , Strube, Michael (Author) , Wienhard, Anna (Author)
Format: Article (Journal) Chapter/Article
Language:English
Published: 9 Jun 2021
In: Arxiv
Year: 2021, Pages: 1-28
DOI:10.48550/arXiv.2106.04941
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.48550/arXiv.2106.04941
Verlag, lizenzpflichtig, Volltext: http://arxiv.org/abs/2106.04941
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Author Notes:Federico López, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard

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