Graph Signal Processing (GSP) extends classical signal processing to data defined on irregular domains represented by graphs. In GSP, measurements or features are treated as signals on the vertices of ...

Probabilistic graph query processing techniques address the challenge of querying networks in which the presence of nodes or edges is uncertain. Such graphs arise in domains as varied as ...

Biden administration officials may have sought to dodge public records laws and congressional oversight by classifying taxpayer-backed loans to Planned Parenthood as “Benghazi,” according to findings ...

There is a quiet failure mode that lives at the center of every AI-assisted coding workflow. You ask Claude Code, Cursor, or Windsurf to modify a function. The agent does it confidently, cleanly, and ...

Abstract: Graph signal recovery (GSR) is a fundamental problem in graph signal processing, where the objective is to reconstruct a complete signal defined over a graph from a subset of noisy or ...

Abstract: Graph signal processing (GSP) provides a principled framework for analyzing signals on graph-structured data. Building on this foundation, graph neural networks (GNNs) extend classical ...

The threat actor known as Harvester has been attributed to a new Linux version of its GoGra backdoor deployed as part of attacks likely targeting entities in South Asia. "The malware uses the ...

A critical security vulnerability has been disclosed in a Python-based sandbox called Terrarium that could result in arbitrary code execution. The vulnerability, tracked as CVE-2026-5752, is rated 9.3 ...