Juan Pablo Vigneaux

Mathematician

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Currently, I am an Olga Taussky and John Todd Instructor in Mathematics at Caltech, mentored by Matilde Marcolli. We co-organize the Information, Geometry, and Physics Seminar.

Previously, I was a postdoctoral researcher at the Max Planck Institute for Mathematics in the Sciences. In 2019, I obtained my Ph.D. in Mathematics at the University of Paris under the supervision of Daniel Bennequin.

I’m broadly interested in mathematical aspects of information theory, particularly in connection with category theory and geometry (metric geometry, geometric measure theory, …).

My published work can be divided in three different areas:

  • Characterization of information measures, mainly information topology.
  • Information dimension and measures with geometric structure.
  • Magnitude and diversity.

I’m currently mostly working on explainable AI and mechanistic interpretability of neural networks. For further details, see the research section.

Here’s my academic CV.

latest posts

selected publications

  1. Journal
    Information theory with finite vector spaces
    Juan Pablo Vigneaux
    IEEE Transactions on Information Theory, 2019
  2. Journal
    Typicality for stratified measures
    Juan Pablo Vigneaux
    IEEE Transactions on Information Theory, 2023
  3. Journal
    Information structures and their cohomology
    Juan Pablo Vigneaux
    Theory and Applications of Categories, 2020
  4. Journal
    A formula for the categorical magnitude in terms of the Moore-Penrose pseudoinverse
    Stephanie Chen, and Juan Pablo Vigneaux
    Bulletin of the Belgian Mathematical Society - Simon Stevin, 2023
    To appear in Vol. 30, Issue 3