EurekAlert!

A survey of geometric graph neural networks: data structures, models and applications

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.

New AI uncovers hidden patterns in biomedical knowledge graphs

A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
C&EN

Integrating ESM-2 and Graph Neural Networks with AlphaFold-2 Structures for Enhanced Protein Function Prediction

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
Frontiers

DGAT: a dynamic graph attention neural network framework for EEG emotion recognition

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...
IEEE

Attentional Graph Neural Network Is All You Need for Robust Massive Network Localization

Abstract: In this paper, we design Graph Neural Networks (GNNs) with attention mechanisms to tackle an important yet challenging nonlinear regression problem: massive network localization. We first ...
IEEE

Automated Design for Hardware-Aware Graph Neural Networks on Edge Devices

Abstract: Graph neural networks (GNNs) have demonstrated significant advantages in handling data from non-Euclidean domains. Given the successful application of neural architecture search (NAS) in ...
Frontiers

User recommendation method integrating hierarchical graph attention network with multimodal knowledge graph

1 Business College, California State University, Long Beach, CA, United States 2 School of Business and Management, Shanghai International Studies University, Shanghai, China In common graph neural ...
Oak Ridge National Lab

GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism...

Proceedings of The Eighth Annual Conference on Machine Learning and Systems Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their ...