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20072025
most citedRobust Topological Inference: Distance To a Measure and Kernel Distance

107 citations · 416 across the 27 of their papers we have counts for

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10 papers · 1 filter

math.ST2025

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…

math.ST2024

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…

math.ST2023

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…

math.ST2020★ 6 cited

Optimal quantization of the mean measure and applications to statistical learning

Frédéric Chazal, Clément Levrard, Martin Royer

This paper addresses the case where data come as point sets, or more generally as discrete measures. Our motivation is twofold: first we intend to approximate with a compactly supp…

math.ST2017

An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists

Frédéric Chazal, Bertrand Michel

Topological Data Analysis is a recent and fast growing field providing a set of new topological and geometric tools to infer relevant features for possibly complex data. This paper…

math.ST2017

Estimating the Reach of a Manifold

Eddie Aamari, Jisu Kim, Frédéric Chazal +3

Various problems in manifold estimation make use of a quantity called the reach, denoted by , which is a measure of the regularity of the manifold. This paper is the first in…