In this tutorial, we build a fully offline Graphify workflow that turns a realistic multi-module Python application into a knowledge graph. We start by installing Graphify and supporting graph ...
Abstract: Graph fraud detection (GFD) is a challenging semi-supervised binary classification task that leverages graph neural networks (GNNs) to identify fraud nodes. However, most existing spectral ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design. In addition, Nature has recently ...
Classification constitutes a fundamental cognitive challenge for both biological and artificial intelligence systems. Here, we investigated how the brain categorizes stimuli that are not linearly ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Graph neural networks (GNNs) have emerged as a powerful tool in predicting molecular ...
Abstract: In this letter, we propose a meta-learning-based fast adversarial training method to address the vulnerability of graph neural network (GNN) based resource allocation method to adversarial ...
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