107 citations · 416 across the 27 of their papers we have counts for
13 papers · 1 filter
Topological phase estimation method for reparameterized periodic functions
Thomas Bonis, Frédéric Chazal, Bertrand Michel +1
We consider a signal composed of several periods of a periodic function, of which we observe a noisy reparametrisation. The phase estimation problem consists of finding that repara…
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds
Thibault de Surrel, Felix Hensel, Mathieu Carrière +5
The use of topological descriptors in modern machine learning applications, such as Persistence Diagrams (PDs) arising from Topological Data Analysis (TDA), has shown great potenti…
Optimizing persistent homology based functions
Mathieu Carrière, Frédéric Chazal, Marc Glisse +2
Solving optimization tasks based on functions and losses with a topological flavor is a very active, growing field of research in data science and Topological Data Analysis, with a…
ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning
Martin Royer, Frédéric Chazal, Clément Levrard +2
Robust topological information commonly comes in the form of a set of persistence diagrams, finite measures that are in nature uneasy to affix to generic machine learning framework…
DTM-based Filtrations
Hirokazu Anai, Frédéric Chazal, Marc Glisse +4
Despite strong stability properties, the persistent homology of filtrations classically used in Topological Data Analysis, such as, e.g. the Cech or Vietoris-Rips filtrations, are…
The density of expected persistence diagrams and its kernel based estimation
Frédéric Chazal, Vincent Divol
Persistence diagrams play a fundamental role in Topological Data Analysis where they are used as topological descriptors of filtrations built on top of data. They consist in discre…