Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Bedart, Dominique"'
Publikováno v:
2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Nov 2021, The Hague, Netherlands
2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Nov 2021, The Hague, Netherlands
International audience; Graph autoencoders (GAE), also known as graph embedding methods, learn latent representations of the nodes of a graph in a low-dimensional space where the structural information is preserved. While real-world graphs are genera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4fb44965e56a986be4e68a0513a0f3cd
https://doi.org/10.1145/3487351.3488333
https://doi.org/10.1145/3487351.3488333
Publikováno v:
French Regional Conference on Complex Systems
French Regional Conference on Complex Systems, May 2021, Dijon, France
French Regional Conference on Complex Systems, May 2021, Dijon, France
International audience; Graph embedding aims to learn a representation of graphs' nodes in a latent low-dimensional space. The purpose is to encode the graph's structural information. While the majority of real-world networks are dynamic, literature
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::40cd6c897656c82ff752e006516e9cdd
https://hal.archives-ouvertes.fr/hal-03274101
https://hal.archives-ouvertes.fr/hal-03274101
Publikováno v:
SN Computer Science; November 2023, Vol. 4 Issue: 6
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed