Graph data, e.g., social and biological networks, financial transactions, knowledge graphs, and transportation systems are pervasive in the natural world, where nodes are entities with features, and ...

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

To achieve true autonomy, AI systems must integrate both neural networks (for learning and pattern recognition) and symbolic AI (for structured knowledge and reasoning). This fusion, known as ...

Built on App Orchid’s semantic knowledge graph, the Agent continuously learns from context to improve accuracy, transparency, and enterprise trust. SAN RAMON, CA / ACCESS Newswire / November 3, 2025 / ...

Chemical separation, including gas separation, is a common process that is required for manufacturing and research. It accounts for a whopping 15 percent of U.S. energy consumption and produces ...