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Mathematics

D-Index
42
Citations
7164
World Ranking
1793
National Ranking
104

Overview

Frédéric Chazal is affiliated with the French Institute for Research in Computer Science and Automation (INRIA) in France. Their research spans several areas within computer science and molecular biology, with a particular focus on topological and geometric data analysis.

The main fields of study associated with Chazal include:

  • Computer Science
  • Biochemistry, Genetics and Molecular Biology

Their work relates to various subfields, including:

  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Biophysics
  • Molecular Biology

Key research topics addressed in their publications are:

  • Topological and Geometric Data Analysis
  • Cell Image Analysis Techniques
  • Advanced Neuroimaging Techniques and Applications
  • Single-cell and Spatial Transcriptomics
  • Fractal and DNA Sequence Analysis
  • Image Retrieval and Classification Techniques
  • Machine Learning and Algorithms

Chazal has authored multiple papers, notable recent publications include:

  • "An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists" (2021, Frontiers in Artificial Intelligence)
  • "Optimizing persistent homology based functions" (2020, arXiv (Cornell University))
  • "PLLay: Efficient Topological Layer based on Persistence Landscapes" (2020, arXiv (Cornell University))
  • "Topological Data Analysis and its usefulness for precision medicine studies" (2022, HAL (Le Centre pour la Communication Scientifique Directe))
  • "Optimal quantization of the mean measure and applications to statistical learning" (2020, arXiv (Cornell University))

Frequent collaborators in their research include:

  • Bertrand Michel
  • Clément Levrard
  • Martin Royer
  • Wojciech Reise
  • Marc Glisse

Publications by Chazal appear regularly in venues such as:

  • arXiv (Cornell University)
  • Frontiers in Artificial Intelligence
  • Electronic Journal of Statistics
  • HAL (Le Centre pour la Communication Scientifique Directe)
  • BMC Bioinformatics

Best Publications

  • An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists

    Frédéric Chazal;Bertrand Michel

  • Proximity of persistence modules and their diagrams

    Frédéric Chazal;David Cohen-Steiner;Marc Glisse;Leonidas J. Guibas

  • The Structure and Stability of Persistence Modules

    Frédéric Chazal;Vin de Silva;Marc Glisse;Steve Oudot

  • Persistence-Based Clustering in Riemannian Manifolds

    Frédéric Chazal;Leonidas J. Guibas;Steve Y. Oudot;Primoz Skraba

  • Gromov-Hausdorff stable signatures for shapes using persistence

    Frédéric Chazal;David Cohen-Steiner;Leonidas J. Guibas;Facundo Mémoli

  • Persistence stability for geometric complexes

    Frédéric Chazal;Vin de Silva;Steve Y. Oudot

  • The λ-medial axis

    Frédéric Chazal;André Lieutier

  • A Sampling Theory for Compact Sets in Euclidean Space

    Frédéric Chazal;David Cohen-Steiner;André Lieutier

  • Geometric Inference for Probability Measures

    Frédéric Chazal;David Cohen-Steiner;Quentin Mérigot

  • Towards persistence-based reconstruction in euclidean spaces

    Frédéric Chazal;Steve Yann Oudot

  • Map-based exploration of intrinsic shape differences and variability

    Raif M. Rustamov;Maks Ovsjanikov;Omri Azencot;Mirela Ben-Chen

  • Persistence-based segmentation of deformable shapes

    Primoz Skraba;Maks Ovsjanikov;Frederic Chazal;Leonidas Guibas

  • Molecular shape analysis based upon the morse-smale complex and the connolly function

    F. Cazals;F. Chazal;T. Lewiner

  • Persistence-Based Structural Recognition

    Chunyuan Li;Maks Ovsjanikov;Frederic Chazal

  • Stochastic Convergence of Persistence Landscapes and Silhouettes

    Frédéric Chazal;Brittany Terese Fasy;Fabrizio Lecci;Alessandro Rinaldo

  • Robust Topological Inference: Distance To a Measure and Kernel Distance

    Frédéric Chazal;Brittany Terese Fasy;Fabrizio Lecci;Bertrand Michel

  • Computing and processing correspondences with functional maps

    Maks Ovsjanikov;Etienne Corman;Michael Bronstein;Emanuele Rodolà

  • Weak feature size and persistent homology: computing homology of solids in Rn from noisy data samples

    Frédéric Chazal;André Lieutier

  • Metric graph reconstruction from noisy data

    Mridul Aanjaneya;Frederic Chazal;Daniel Chen;Marc Glisse

  • Geometric and Topological Inference

    Jean-Daniel Boissonnat;Frédéric Chazal;Mariette Yvinec

  • Metric Graph Reconstruction From Noisy Data

    Mridul Aanjaneya;Frédéric Chazal;Daniel Chen;Marc Glisse

  • Stochastic convergence of persistence landscapes and silhouettes

    Frédéric Chazal;Brittany Terese Fasy;Fabrizio Lecci;Alessandro Rinaldo

Frequent Co-Authors

David Cohen-Steiner
David Cohen-Steiner French Institute for Research in Computer Science and Automation - INRIA
Larry Wasserman
Larry Wasserman Carnegie Mellon University
Alessandro Rinaldo
Alessandro Rinaldo The University of Texas at Austin
Leonidas J. Guibas
Leonidas J. Guibas Stanford University
Maks Ovsjanikov
Maks Ovsjanikov École Polytechnique
Mirela Ben-Chen
Mirela Ben-Chen Technion – Israel Institute of Technology
Aarti Singh
Aarti Singh Carnegie Mellon University
Jian Sun
Jian Sun Megvii
Tamal K. Dey
Tamal K. Dey Purdue University West Lafayette
Jean-Daniel Boissonnat
Jean-Daniel Boissonnat Université Côte d'Azur

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