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Many applications rely upon graphical data, which standard machine learning methods such as feedforward networks and convolutions cannot handle. GFNs present a novel approach of tackling this problem ...

Abstract: Including Artificial Neural Networks in embedded systems at the edge allows applications to exploit Artificial Intelligence capabilities directly within devices operating at the network ...

This important study provides a comprehensive map of how touch-sensitive neurons in the fly head connect to downstream circuits, revealing parallel pathways that preserve spatial organization and ...

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