AI-powered knowledge graph links heart images to genes and drug predictions

Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already ...
Devdiscourse

AI takes the helm in power systems facing renewable and carbon pressures

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...
EurekAlert!

Accelerated streaming subgraph matching framework is faster, more robust, and scalable

Graphs are widely used to represent complex relationships in everyday applications such as social networks, bioinformatics, ...
IEEE

UPN-GCN: Update Positive-Negative Graph Convolution Neural Network in Non-Euclidean Structured Data

Abstract: Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have ...
IEEE

Multiscale Spatiotemporal Graph Convolutional Networks With Dynamic Delay Awareness for Traffic Forecasting

Abstract: The spatiotemporal dynamics of traffic forecasting make it a challenging task. In recent years, by adapting to the topology of traffic networks where road segments serve as nodes, graph ...
The New York Times

30 Charts That Show How Covid Changed Everything

Covid-19 broke the charts. Decades from now, the pandemic will be visible in the historical data of nearly anything measurable today: an unmistakable spike, dip or jolt that officially began for ...