Tufin will showcase these exciting new agents along with its other TufinAI-powered capabilities and its vision for Multi-Vendor Agentic Network Security, at the upcoming RSA Conference 2026 (RSAC), ...

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 ...

Giulia Livieri sets out remarkable new research with results that clarify how learning works on complex graphs and how quickly any method (including Graph Convolutional Networks) can learn from them, ...

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...

One theme cuts across the most credible 2026 predictions: autonomy will be driven less by bigger models and more by better ...

In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these ...