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The paper presents a Graph Attention Convolutional Network (GACN) for flow reconstruction from very sparse data in time-varying geometries. The model incorporates a feature propagation algorithm as a preprocessing step to handle extremely sparse inpu
Externí odkaz:
http://arxiv.org/abs/2411.08764
Autor:
Pérez-Schael, Irene, Guntiñas, MarÃa J., Pérez, Mireya, Pagone, Vito, Rojas, Ana M., González, Rosabel, Cunto, Walter, Hoshino, Yasutaka, Kapikian, Albert Z.
Publikováno v:
New England Journal of Medicine. 10/23/97, Vol. 337 Issue 17, p1181-1187. 1p.
