Frederic Chazal

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Steve OudotInriaVerified email at inria.fr
David Cohen-SteinerresearcherVerified email at sophia.inria.fr
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Bertrand MICHELEcole Centrale de Nantes , Nantes UniversitéVerified email at ec-nantes.fr
Maks OvsjanikovEcole Polytechnique, Google DeepMindVerified email at lix.polytechnique.fr
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Mirela Ben-ChenProfessor, Technion - Israel Institute of TechnologyVerified email at cs.technion.ac.il
Brittany Terese FasyMontana State UniversityVerified email at fasy.us
Fabrizio LecciColumbia UniversityVerified email at columbia.edu
Quentin MerigotUniversité Paris-SaclayVerified email at universite-paris-saclay.fr
Facundo MémoliDepartment of Mathematics. Rutgers University.Verified email at rutgers.edu
Mickaël BuchetGraz University of TechnologyVerified email at tugraz.at
Jarek RossignacProfessor of Computer Science, Georgia Institute of TechnologyVerified email at cc.gatech.edu
Donald R. SheehyNorth Carolina State UniversityVerified email at ncsu.edu
Raif RustamovAT&T Labs Research, Principal Inventive ScientistVerified email at research.att.com
Thomas LewinerProfessor of Mathematics, PUC-RioVerified email at puc-rio.br
Chunyuan LixAIVerified email at x.ai
William Crawley-BoeveyUniversität BielefeldVerified email at math.uni-bielefeld.de
Luc DevroyeMcGill UniversityVerified email at cs.mcgill.ca
Gérard BiauProfessor, Sorbonne University, ParisVerified email at sorbonne-universite.fr

Frederic Chazal

INRIA Saclay - Ile de France

Verified email at inria.fr - Homepage

computational topology and geometry statistics topological data analysis machine learning


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An introduction to topological data analysis: fundamental and practical aspects for data scientists F Chazal, B Michel Frontiers in artificial intelligence 4, 667963, 2021	766	2021
The structure and stability of persistence modules F Chazal, V De Silva, M Glisse, S Oudot Springer 10, 978-3, 2016	652	2016
Proximity of persistence modules and their diagrams F Chazal, D Cohen-Steiner, M Glisse, LJ Guibas, SY Oudot Proceedings of the twenty-fifth annual symposium on Computational geometry …, 2009	603	2009
Persistence-based clustering in Riemannian manifolds F Chazal, LJ Guibas, SY Oudot, P Skraba Journal of the ACM (JACM) 60 (6), 1-38, 2013	386	2013
Persistence stability for geometric complexes F Chazal, V De Silva, S Oudot Geometriae Dedicata 173 (1), 193-214, 2014	365	2014
Gromov‐Hausdorff stable signatures for shapes using persistence F Chazal, D Cohen‐Steiner, LJ Guibas, F Mémoli, SY Oudot Computer Graphics Forum 28 (5), 1393-1403, 2009	361	2009
Geometric inference for probability measures F Chazal, D Cohen-Steiner, Q Mérigot Foundations of Computational Mathematics 11, 733-751, 2011	317*	2011
The “λ-medial axis” F Chazal, A Lieutier Graphical models 67 (4), 304-331, 2005	260	2005
A sampling theory for compact sets in Euclidean space F Chazal, D Cohen-Steiner, A Lieutier Proceedings of the twenty-second annual symposium on Computational geometry …, 2006	254	2006
Towards persistence-based reconstruction in Euclidean spaces F Chazal, SY Oudot Proceedings of the twenty-fourth annual symposium on Computational geometry …, 2008	246	2008
Perslay: A simple and versatile neural network layer for persistence diagrams M Carriere, F Chazal, IS Datashape, Y Ike, T Lacombe, M Royer, ... stat 1050, 5, 2019	239*	2019
Stochastic convergence of persistence landscapes and silhouettes F Chazal, BT Fasy, F Lecci, A Rinaldo, L Wasserman Proceedings of the thirtieth annual symposium on Computational geometry, 474-483, 2014	234	2014
Geometric and topological inference JD Boissonnat, F Chazal, M Yvinec Cambridge University Press, 2018	222	2018
Map-based exploration of intrinsic shape differences and variability RM Rustamov, M Ovsjanikov, O Azencot, M Ben-Chen, F Chazal, ... ACM Transactions on Graphics (TOG) 32 (4), 1-12, 2013	169	2013
Robust topological inference: Distance to a measure and kernel distance B Fasy, F Lecci, L Wasserman Journal of Machine Learning Research 18 (159), 1-40, 2018	168	2018
Persistence-based segmentation of deformable shapes P Skraba, M Ovsjanikov, F Chazal, L Guibas 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010	165	2010
Computing and processing correspondences with functional maps M Ovsjanikov, E Corman, M Bronstein, E Rodolà, M Ben-Chen, L Guibas, ... SIGGRAPH ASIA 2016 Courses, 1-60, 2016	152	2016
Persistence-based structural recognition C Li, M Ovsjanikov, F Chazal Proceedings of the IEEE conference on computer vision and pattern …, 2014	152	2014
Molecular shape analysis based upon the Morse-Smale complex and the Connolly function F Cazals, F Chazal, T Lewiner Proceedings of the nineteenth annual symposium on Computational geometry …, 2003	152	2003
Scalar field analysis over point cloud data F Chazal, LJ Guibas, SY Oudot, P Skraba Discrete & Computational Geometry 46 (4), 743-775, 2011	149*	2011

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