Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it makes ...

In the modern world of data-driven applications we are at a fascinating point at which both fully formed products and powerful components are being offered to us at a breathtaking pace. The question ...

Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks ...

Before talking about best practices for visually presenting scientific data, it is important to summarize and define what tools are available. For most fields, graphs are the most common form of ...