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  1. www.mlwright.org › persistencePersistent Homology: Matthew Wright

    Persistent homology can identify significant topological features of data. In this context, data usually means a cloud of points, often representing measurements of some object, and possibly occurring in a high-dimensional space. Topological features include clusters, loops, and voids.

    • Topological Integrals

      Non-Technical Analogy. The mathematician Stephen Schanuel...

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      office. Regents Hall of Mathematical Sciences, room 405....

    • Research

      The goal of my research is to develop mathematical, and...

    • Papers

      Persistent homology, an algebraic method for discerning...

    • Presentations

      Matthew Wright works in the areas of applied and...

    • Stochastic Geometry

      Randomness. The word stochastic refers to things that...

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    • Computing Persistent Homology Matthew L Wright Institute for
    • Matthew Wright (10/20/15): Visualizing 2 Dimensional Persistent ...
    • An introduction to persistent homology - YouTube

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  3. www.mlwright.org › papersPapers: Matthew Wright

    Persistent homology, an algebraic method for discerning structure in abstract data, relies on the construction of a sequence of nested topological spaces known as a filtration. Two-parameter persistent homology allows the analysis of data simultaneously filtered by two parameters, but requires a bifiltration -- a sequence of topological spaces ...

  4. www.mlwright.org › docs › cv_webMATTHEW L. WRIGHT

    is on the computation and visualization of multiparameter persistent homology and its use in the analysis of complex data. I also study topological and geometric integrals and their applications.

  5. drops.dagstuhl.de › entities › documentIntroduction to Persistent Homology

    Jun 10, 2016 · Persistent homology is an algebraic method of discerning the topological features of complex data, which in recent years has found applications in fields such as image processing and biological systems.

  6. arxiv.org › pdf › 2207Anway De, Thong Vo, Matthew Wright July 8, 2022 - arXiv.org

    In this paper, we lay groundwork for two-parameter persistent homology of digital images by proposing and analyzing a bi ltration that captures both intensity and distance information from digital images.

  7. arxiv.org › pdf › 2007Duke University, xz264@duke.edu arXiv:2007.00063v2 [math.AT ...

    Persistent homology, a primary tool of TDA, is used to discern geometric and topological structure in high-dimensional datasets. While single-parameter persistent homology has been widely used, multi-parameter variants of persistent homology are especially appealing, not only for

  8. scholar.google.com › citations‪Matthew L Wright‬ - ‪Google Scholar‬

    Computing minimal presentations and bigraded betti numbers of 2-parameter persistent homology