Unlike traditional databases, knowledge graphs organize information as nodes and edges, making them better for AI systems that reason & infer.

In these graphs, vertices typically represent non-central elements of a group, and an edge connects two vertices if the corresponding elements commute. This approach not only provides insights ...

In these graphs, vertices represent group elements and edges connect each element with those obtained by multiplying with members of a specified generating set. Perfect codes, originally conceived ...

Our lives are nodes in that grand web of interactions.” “Dots and Lines” is about modern network science. “At their most ...

However, the rapid growth of wireless networks has brought about massive data traffic, which hinders the application of traditional optimization theory-based algorithms. Meanwhile, traditional graph .

Analyze the time and space complexity of your solution. Compare your solution to others and identify areas for improvement. Refactor your code for readability and maintainability. Document your code ...

Abstract: Let G = (V, E) be an undirected graph, where V is the vertex set and E is the edge set. A subset M of E is an induced ... In this paper, we introduce a maximum induced matching algorithm in ...

PepGen leverages a graph-based approach to improve the detection of hidden protein variants in a computationally efficient ...

Scientists have uncovered how close we can get to perfect optical precision using AI, despite the physical limitations imposed by light itself. By combining physics theory with neural networks trained ...

Research has shown that large language models (LLMs) tend to overemphasize information at the beginning and end of a document ...