Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Najafi, Bahareh"'
Publikováno v:
Mach. Learn. Knowl. Extr. 2022, 4(2), 397-417
GNNs have been proven to perform highly effective in various node-level, edge-level, and graph-level prediction tasks in several domains. Existing approaches mainly focus on static graphs. However, many graphs change over time with their edge may dis
Externí odkaz:
http://arxiv.org/abs/2108.03400
Publikováno v:
2020 92nd IEEE conference on vehicular technology
Missing data is a challenge in many applications, including intelligent transportation systems (ITS). In this paper, we study traffic speed and travel time estimations in ITS, where portions of the collected data are missing due to sensor instability
Externí odkaz:
http://arxiv.org/abs/2101.03295
Publikováno v:
Machine Learning & Knowledge Extraction; Dec2023, Vol. 5 Issue 4, p1359-1381, 23p
Additional file 1. Interview Guide.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3127ed5be03c43cf215956f696622741
Akademický článek
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Publikováno v:
Machine Learning & Knowledge Extraction; Jun2022, Vol. 4 Issue 2, p397-417, 21p
Autor:
Najafi, Bahareh1, Mojab, Faraz2, Ghaderi, Loghman3, Farhadifar, Fariba4, Roshani, Daem5, Seidi, Jamal6 jamal.seidi@muk.ac.ir
Publikováno v:
Journal of Clinical & Diagnostic Research. Nov2017, Vol. 11 Issue 11, p1-4. 4p.