Discrete Morse-based Graph Skeletonization and Data Analysis

Discrete Morse-based Graph Skeletonization and Data Analysis
by Yusu Wang

Abstract:
In recent years, topological and geometric data analysis (TGDA) has emerged as a new and promising field for processing, analyzing and understanding complex data. Indeed, geometry and topology form natural platforms for data analysis, with geometry describing the ”shape” and ”structure” behind data; and topology characterizing / summarizing both the domain where data are sampled from, as well as functions and maps associated to them. In this talk, Yusu will show how the topological objects and ideas can be combined with algorithmic developments to lead to new approaches for inferring hidden graph skeleton structure behind (low and high dimensional) data; as well as how they can be combined with machine learning pipelines for further data analysis tasks (e.g., to neuroscience and to material science). This talk is based on multiple projects with multiple collaborators and references will be given during the talk.

Bio:

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Agenda (Pacific Daylight Time, UTC -07)
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- 5:30 - 5:40 pm -- Gathering and introductions
- 5:40 - 6:30 pm -- Talk
- 6:30 - 7:00 pm -- Q & A, discussion

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Questions?
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