Graph Theory Matrix Approach (GTMA) is moving with great speed into the main stream of computer design, Information sciences, Information and Computer programming, Artificial Intelligence and design, ...

Human brain connectivity is complex. Graph-theory-based analysis has become a powerful and popular approach for analyzing brain imaging data, largely because of its potential to quantitatively ...

Context engineering—the art of shaping the data, metadata, and relationships that feed AI—may become the most critical ...

Syllabus: The NTA has put the official JEE Main 2026 Syllabus online on their website: jeemain.nta.nic.in. If you're planning ...

This text gives a reasonably deep account of material closely related to engineering applications. Topics like directed-graph solutions of linear equations, topological analysis of linear systems, ...

A familiarity with matrices is necessary nowadays in many areas of mathematics and in a wide variety of other disciplines. Areas of mathematics where matrices occur include algebra, differential ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Researchers are using machine learning, symbolic regression, and high-performance computing to explore and classify string ...

Twisted materials—known as moiré structures—have revolutionized modern physics, emerging as today's "alchemy" by creating ...

Graph Neural Networks (GNNs) are a recent family of Neural Network models specifically designed to harness the inherent structure and dependencies present in graph-structured data, revolutionizing the ...