Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Robin Devooght"'
Autor:
Bram Van Moorter, Ilkka Kivimäki, Andreas Noack, Robin Devooght, Manuela Panzacchi, Kimberly R. Hall, Pierre Leleux, Marco Saerens
Publikováno v:
Methods in Ecology and Evolution, Vol 14, Iss 1, Pp 133-145 (2023)
Abstract Increasingly precise spatial data (e.g. high‐resolution imagery from remote sensing) allow for improved representations of the landscape network for assessing the combined effects of habitat loss and connectivity declines on biodiversity.
Externí odkaz:
https://doaj.org/article/02776583e4384ed49440ee1f8458c702
Autor:
null Bram Van Moorter, null Ilkka Kivimäki, null Andreas Noack, null Robin Devooght, null Manuela Panzacchi, null Kimberly R. Hall, null Pierre Leleux, null Marco Saerens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1e57a23dd23ee2d64c1ecf3b623c8c0
https://doi.org/10.1111/2041-210x.13850/v2/response1
https://doi.org/10.1111/2041-210x.13850/v2/response1
Autor:
Bram Van Moorter, Ilkka Kivimäki, Andreas Noack, Robin Devooght, Manuela Panzacchi, Kimberly R. Hall, Pierre Leleux, Marco Saerens
Publikováno v:
Methods in Ecology and Evolution
Increasingly precise spatial data (e.g. high-resolution imagery from remote sensing) allow for improved representations of the landscape network for assessing the combined effects of habitat loss and connectivity declines on biodiversity. However, ev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c291bf2ab80553e4515f2967dc2d5d2f
https://hdl.handle.net/11250/3049409
https://hdl.handle.net/11250/3049409
Autor:
Hugues Bersini, Robin Devooght
Publikováno v:
UMAP
Recurrent neural networks have recently been successfully applied to the session-based recommendation problem, and is part of a growing interest for collaborative filtering based on sequence prediction. This new approach to recommendations reveals an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1624c714787f1b649511ea5e5937d179
https://doi.org/10.1145/3079628.3079670
https://doi.org/10.1145/3079628.3079670
Publikováno v:
KDD
Advanced and effective collaborative filtering methods based on explicit feedback assume that unknown ratings do not follow the same model as the observed ones (\emph{not missing at random}). In this work, we build on this assumption, and introduce a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d78b8da898b45c5c46c6f0337286a4f9
Autor:
Marco Saerens, Ilkka Kivimäki, Amin Mantrach, Alejandro Jaimes, Robin Devooght, Hugues Bersini
Publikováno v:
WWW
Although criticized for some of its limitations, modularity remains a standard measure for analyzing social networks. Quantifying the statistical surprise in the arrangement of the edges of the network has led to simple and powerful algorithms. Howev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::967a443ec812a96127e2ad1ff6094e19
https://doi.org/10.1145/2566486.2567986
https://doi.org/10.1145/2566486.2567986