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Applications of Topological Data Analysis to Cosmology and Beyond

Jun 5 – 9, 2023
IFPU
Europe/Rome timezone

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Contribution List

18 out of 18 displayed
  1. 1. Introduction to Workshop
    Matteo Biagetti (SISSA)
    6/5/23, 10:00 AM
  2. 18. Persistent Homology of Cosmic Structures
    Matteo Biagetti
    6/5/23, 10:15 AM
  3. 2. Information Maximizing Persistent Homology
    Karthik Viswanathan
    6/5/23, 11:00 AM
  4. 13. Unsupervised learning methods in quantum computers and simulators: why we do it and which methods have been used
    Marcello Dalmonte
    6/5/23, 2:00 PM
  5. 3. Parameter inference using persistent homology
    Sibilla Bouché
    6/6/23, 9:30 AM
  6. 4. Quasars and/or dimensionality reduction
    Gabriella Contardo
    6/6/23, 2:00 PM
  7. 16. Our Attempts to Use Unsupervised Learning in Soft-Matter Physics
    Ali Hassanali
    6/6/23, 3:00 PM
  8. 5. An introduction to Topological Data Analysis
    Mathieu Carrière
    6/7/23, 9:30 AM

    Topological Data Analysis (TDA) is a growing field of research at the intersection of data science and computational geometry and topology. It has encountered key successes in several different applications (ranging from cancer subtype identification in bioinformatics to shape recognition in computer vision, just to name a few), and become the landmark product of several companies in the...

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  9. 6. On the geometry of large transformers representations
    Alberto Cazzaniga
    6/7/23, 11:00 AM
  10. 7. Barcodes for multiparameter persistence
    Magnus Botnan
    6/7/23, 12:00 PM

    Multiparameter persistence is a generalization of persistent homology that allows for more than a single filtration function. Such constructions arise naturally when considering data with outliers or variations in density, time-varying data, or functional data.

    In single-parameter persistence, the barcode is equivalent to the “rank invariant”: the function that associates the rank of...

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  11. 15. What Every Physicist Should Know About String Theory
    Edward Witten
    6/7/23, 2:00 PM

    This event is organized by ICTP.

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  12. 17. Machine learning you can trust for cosmology and astrophysics
    Roberto Trotta
    6/7/23, 4:00 PM
  13. 9. Multiparameter persistence
    Sliem El Ela
    6/8/23, 9:30 AM
  14. 14. Graph-based algorithms
    6/8/23, 2:00 PM
  15. 10. Inverse optimization
    Sliem El Ela
    6/8/23, 3:00 PM
  16. 11. Generative models for cosmological simulations
    Mathieu Carrière
    6/9/23, 9:30 AM
  17. 12. Closing remarks
    6/9/23, 2:00 PM
  18. 8. Coffee break and discussion