Topological Data Analysis (TDA) is an innovative framework that utilises principles from algebraic topology to extract intrinsic patterns and structural features from complex, multi‐dimensional data.

The reliability of data storage and writing speed in advanced magnetic devices depend on drastic, complex changes in microscopic magnetic domain structures. However, it is extremely challenging to ...

Researchers used topological data analysis to improve the predictions of physical properties of amorphous materials by machine-learning algorithms. This may allow for cheaper and faster calculations ...

The talk below, “Topological Data Analysis for the Working Data Scientist” was presented at the SF Data Mining meetup group. Speaker Anthony Bak begins with a short review of the Mapper algorithm and ...

Although machine learning is an integral component of Artificial Intelligence, it’s critical to realize that it’s just one of the many dimensions of this collection of technologies. Expressions of ...

Self-organized pattern behavior is ubiquitous throughout nature, from fish schooling to collective cell dynamics during organism development. Qualitatively these patterns display impressive ...

Topological data analysis. (IMAGE) Tokyo University of Science Caption A new approach to understanding magnetic phenomena and magnetic domain structures better at the microscales, topological data ...