107 citations · 416 across the 27 of their papers we have counts for
36 papers
Fermat Distance-to-Measure: a robust Fermat-like metric
Jérôme Taupin, Frédéric Chazal
Given a probability measure with density, Fermat distances and density-driven metrics are conformal transformations of the Euclidean metric that shrink distances in high density ar…
Topological Analysis for Detecting Anomalies (TADA) in Time Series
Frédéric Chazal, Martin Royer, Clément Levrard
This paper introduces new methodology based on the field of Topological Data Analysis for detecting anomalies in multivariate time series, that aims to detect global changes in the…
Supervised Contamination Detection, with Flow Cytometry Application
Solenne Gaucher, Gilles Blanchard, Frédéric Chazal
The contamination detection problem aims to determine whether a set of observations has been contaminated, i.e. whether it contains points drawn from a distribution different from…
Choosing the parameter of the Fermat distance: navigating geometry and noise
Frédéric Chazal, Laure Ferraris, Pablo Groisman +3
The Fermat distance has been recently established as a useful tool for machine learning tasks when a natural distance is not directly available to the practitioner or to improve th…
Topological signatures of periodic-like signals
Wojciech Reise, Bertrand Michel, Frédéric Chazal
We present a method to construct signatures of periodic-like data. Based on topological considerations, our construction encodes information about the order and values of local ext…
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks
Charles Arnal, Felix Hensel, Mathieu Carrière +4
Despite their successful application to a variety of tasks, neural networks remain limited, like other machine learning methods, by their sensitivity to shifts in the data: their p…