Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...

Researchers at Chiba University in Japan have developed a new artificial intelligence framework capable of decoding complex brain activity with significantly improved accuracy, marking an important ...

Motor imagery electroencephalography (EEG) signals depict changes in brain activity during imagined limb movements. Conventional methods, however, often fail to capture these spatiotemporal variations ...

A research team led by Prof. Zhan Yang from the Shenzhen Institute of Advanced Technology (SIAT) of the Chinese Academy of Sciences, has recently introduced a novel unsupervised dual-stream model ...