Robuta

By exploiting the graph attention network, the authors of this study learn robust node representations of graphs in hyperbolic spaces, utilizing the gyrovector...

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So far, numerous learned models have been pressed to use in microwave imaging problems. These models however, are oblivious to the imaging geometry. It has alwa

RAGC: Residual Attention Graph Convolutional Network for Geometric 3D Scene Classification (ICCVW 2019) - imatge-upc/ragc

Accurate electricity consumption forecasting is essential for power scheduling.

Graph convolution networks (GCNs) have been widely used in the field of skeleton-based human action recognition. However, it is still difficult to improve re...

04/07/23 - With the development of the Internet of Things (IoT), network intrusion detection is becoming more complex and extensive. It is es...