Abstract: Recently, topological graphs based on structural or functional connectivity of brain network have been utilized to construct graph neural networks (GNN) for Electroencephalogram (EEG) ...

Abstract: Over the past decade, Channel State Information (CSI)-based human activity recognition (HAR) has attracted wide attention. Despite significant advancements, existing CSI-based HAR methods ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...

The shoe box-sized device, dubbed CL1, is a notable departure from a conventional computer, and uses human brain cells to run fluid neural networks. In 2022, Cortical Labs made a big splash after ...

Our brain’s memory center bears a sleek design. A peek into living tissue from human hippocampi, a brain region crucial for memory and learning, revealed relatively few cell-to-cell connections for ...

A Deep Neural Network (DNN) is an artificial neural network that features multiple layers of interconnected nodes, also known as neurons. These layers include an input, multiple hidden, and output ...