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pro vyhledávání: '"Djellabi, Mehdi"'
Autor:
Thabet, Slimane, Djellabi, Mehdi, Sokolov, Igor, Kasture, Sachin, Henry, Louis-Paul, Henriet, Loïc
In this work, we propose novel families of positional encodings tailored to graph neural networks obtained with quantum computers. These encodings leverage the long-range correlations inherent in quantum systems that arise from mapping the topology o
Externí odkaz:
http://arxiv.org/abs/2406.06547
Autor:
Dalyac, Constantin, Leclerc, Lucas, Vignoli, Louis, Djellabi, Mehdi, Coelho, Wesley da Silva, Ximenez, Bruno, Dareau, Alexandre, Dreon, Davide, Elfving, VIncent E., Signoles, Adrien, Henry, Louis-Paul, Henriet, Loïc
Neutral atom technology has steadily demonstrated significant theoretical and experimental advancements, positioning itself as a front-runner platform for running quantum algorithms. One unique advantage of this technology lies in the ability to reco
Externí odkaz:
http://arxiv.org/abs/2403.11931
Autor:
Thabet, Slimane, Fouilland, Romain, Djellabi, Mehdi, Sokolov, Igor, Kasture, Sachin, Henry, Louis-Paul, Henriet, Loïc
Transformers are increasingly employed for graph data, demonstrating competitive performance in diverse tasks. To incorporate graph information into these models, it is essential to enhance node and edge features with positional encodings. In this wo
Externí odkaz:
http://arxiv.org/abs/2310.20519
Autor:
Djellabi, Mehdi, Jouve, Bertrand
Stream graphs are a very useful mode of representation for temporal network data, whose richness offers a wide range of possible approaches. The various methods aimed at generalising the classical approaches applied to static networks are constantly
Externí odkaz:
http://arxiv.org/abs/2104.05982
Local interaction measures for the nodes of a complex network : theoretical and practical approaches
Autor:
Djellabi, Mehdi
Publikováno v:
Autre [cs.OH]. Université Toulouse le Mirail-Toulouse II, 2021. Français. ⟨NNT : 2021TOU20013⟩
This thesis studies the structure of large real networks. Many studies have shown that the properties of systems composed of interacting elements can be extracted from the structure of their network. For this reason, different families of algorithms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::798d0aff5a966ae7be0c241043e8c32a
https://theses.hal.science/tel-03435240
https://theses.hal.science/tel-03435240
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