The graph below shows the total number of publications each year in Graph Algorithms and Convexity Parameters. References [1] Integer programming models and polyhedral study for the geodesic ...

Dijkstra’s algorithm was long thought to be the most efficient way to find a graph’s best routes. Researchers have now proven that it’s “universally optimal.” ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

Now a trio of computer scientists has solved this long-standing problem. Their new algorithm, which finds the shortest paths through a graph from a given “source” node to every other node, nearly ...

Deep learning defined. Deep learning is a form of machine learning that models patterns in data as complex, multi-layered networks. Because deep learning is the most general way to model a problem ...

Proposed AI Governance Model For Healthcare. Given the complexity and challenges surrounding AI adoption, a thoughtful and well-rounded governance model is essential—one that balances regulatory ...

Today Memgraph, the streaming graph application platform, announced Memgraph 2.0, the public launch of its source-available platform, making it easy f ...

About Complex Network and Map Graph Group. Examples of big graph data in the real world include complex networks, such as social networks and the Web graph, and the map graph used to represent traffic ...

Opaque and potentially biased mathematical models are remaking our lives—and neither the companies responsible for developing them nor the government is interested in addressing the problem.