Convolutional neural networks expect a grid that represents the different dimensions of the data they process (e.g., width, height, and color channels of images). Graphs can come in different ...

High-entropy alloys (HEAs) offer tunable compositions and surface structures, presenting significant potential for creating ...

A review by researchers at Tongji University and the University of Technology Sydney published in Frontiers of Computer ...

GNN, a framework to train robust GNNs under noisy conditions. Soft-GNN mitigates label noise impact through dynamic ...

GNNs extend the foundational ideas of Convolutional Neural Networks (CNNs) to graph data. While CNNs capture spatial locality in grid-like data (for example, images) through convolutional kernels, ...

The team develops a new model, GCM, which captures the interactions among multiple user behaviors via graph neural networks, and then models the interactions among features of individual behavior ...

This article is published by AllBusiness.com, a partner of TIME. A Convolutional Neural Network (CNN) represents a sophisticated advancement in artificial intelligence technology, specifically ...