Graph databases such as Neo4j are very different from traditional Structured Query Language-based data platforms such as Oracle and Microsoft SQL. Instead of storing data in tables consisting of ...

Early data suggests that Canada’s real GDP growth went down in Q1 2025, but this does not (yet) indicate a recession as real GDP growth was up the previous quarter. The most common recession ...

Traditional methods have limited performance when extracting features from noisy hyperspectral data. Graph Neural Networks (GNNs) offer an adaptable and robust structure by effectively extracting both ...

Unlike traditional retrieval-augmented generation (RAG) methods, Graphiti continuously integrates user interactions, structured and unstructured enterprise data, and external information into a ...

Timeseries are determined for each Australian State, the Northern Territory and the six regions shown above The actual data values used to produce each graph are available via the "Raw dataset" link.

The actual data values used to produce each graph are available via the "Raw dataset" link. The format for these data is: The "Sorted dataset" link provides the timeseries as a sorted list in order to ...

With the emergence of advanced machine learning, graph-guided neural networks have gained attention for their unique ability to represent structured data and relationships among process variables. By ...

Sea Ice Today began as a way to make sea ice science and analysis more relevant and accessible. In combination, NASA data and NSIDC expertise provide easy-to-use resources and tools to increase our ...

🤖 Deepfake detection using Graph Convolutional Networks (GCNs) to analyze facial landmark graphs. Combines computer vision, graph-based learning, and facial geometry for robust media forensics.