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pro vyhledávání: '"edge prediction"'
This paper introduces a novel method for reconstructing meshes from sparse point clouds by predicting edge connection. Existing implicit methods usually produce superior smooth and watertight meshes due to the isosurface extraction algorithms~(e.g.,
Externí odkaz:
http://arxiv.org/abs/2407.11610
Autor:
Rahmati, Zahed
Despite the success of graph neural network models in node classification, edge prediction (the task of predicting missing or potential links between nodes in a graph) remains a challenging problem for these models. A common approach for edge predict
Externí odkaz:
http://arxiv.org/abs/2311.02921
Akademický článek
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Akademický článek
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Autor:
Jin, Jiarui, Wang, Yangkun, Zhang, Weinan, Gan, Quan, Song, Xiang, Yu, Yong, Zhang, Zheng, Wipf, David
Graph Neural Networks (GNNs), originally proposed for node classification, have also motivated many recent works on edge prediction (a.k.a., link prediction). However, existing methods lack elaborate design regarding the distinctions between two task
Externí odkaz:
http://arxiv.org/abs/2212.12970
Autor:
Umaa Mahesswari G, Uma Maheswari P
Publikováno v:
Heliyon, Vol 10, Iss 20, Pp e39205- (2024)
PolyCystic Ovarian Syndrome (PCOS) poses significant challenges to women's reproductive health due to its diagnostic complexity arising from a variety of symptoms, including hirsutism, anovulation, pain, obesity, hyperandrogenism, and oligomenorrhea,
Externí odkaz:
https://doaj.org/article/b8f2af9a55ca47c4a870e8a65c43501a
Graph neural networks have shown to learn effective node representations, enabling node-, link-, and graph-level inference. Conventional graph networks assume static relations between nodes, while relations between entities in a video often evolve ov
Externí odkaz:
http://arxiv.org/abs/2212.02875
Autor:
Walaa Othman, Nikolay Shilov
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 32, Iss 1, Pp 196-203 (2022)
Today, enterprise modelling is still a highly manual task. There are exist some assistance techniques but they are mostly limited to pattern libraries and pre-defined rules, which limits their functionality and makes them non-flexible. In our previou
Externí odkaz:
https://doaj.org/article/2b363fce0e0244a993a4a1cb02a06d4f
Machine learning and data mining algorithms have been increasingly used recently to support decision-making systems in many areas of high societal importance such as healthcare, education, or security. While being very efficient in their predictive a
Externí odkaz:
http://arxiv.org/abs/2010.16326
Autor:
Metelli, Silvia, Heard, Nicholas
Publikováno v:
The Annals of Applied Statistics, 2019 Dec 01. 13(4), 2586-2610.
Externí odkaz:
https://www.jstor.org/stable/26866735