Full list of publications


Books

J.-D. Boissonnat, F. Chazal, M. Yvinec. Geometric and Topological Inference. Cambridge Texts in Applied Mathematics, vol. 57, Cambridge University Press, 2018.   
F. Chazal, V. de Silva, M. Glisse, S. Oudot. The Structure and Stability of Persistence Modules. Monograph published in SpringerBriefs in Mathematics, Springer, 2016.

Journals

W Reise, B Michel, F Chazal. Topological signatures of periodic-like signals. To appear in Bernoulli, 2024.   
T. Bonis, F. Chazal, B. Michel, W. Reise. Topological phase estimation method for reparameterized periodic functions. To appear in Advances in Computational Mathematics, 2024.   
F. Hensel, C. Arnal, M. Carrière, T. Lacombe, H. Kurihara, Y. Ike, F. Chazal. MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks. To appear in Transactions on Machine Learning Research, 2024.   
F. Chazal, L. Ferraris, P. Groisman, M. Jonckheere, F. Pascal, F. Sapienza. Choosing the parameter of the Fermat distance: navigating geometry and noise. To appear in Transactions on Machine Learning Research, 2024.   
Iniesta, R., Carr, E., Carriere, M., Yerolemou, N., Michel, B. and Chazal, F. Topological Data Analysis and its usefulness for precision medicine studies. In Statistics Operations and Research Transactions (SORT), 46(1), 115-136, 2022.   
F. Chazal, B. Michel. An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists. Frontiers in AI, 2021.   
E. Carr, M. Carrière, B. Michel, F. Chazal, R. Iniesta. Identifying homogeneous subgroups of patients and important features: a topological machine learning approach. BMC Bioinformatics volume 22, Article number: 449 (2021).   
F. Chazal, C. Levrard, M. Royer. Optimal quantization of the mean measure and application to clustering of measures. To appear in Electronic Journal of Statistics, 2021.   
B. Beaufils, F. Chazal, M. Grelet, B. Michel. Stride Detector from Ankle-Mounted Inertial Sensors for Pedestrian Navigation and Activity Recognition with Machine Learning Approaches. Sensors 2019, 19, 4491.   
V. Divol, F. Chazal. The density of expected persistence diagrams and its kernel based estimation. To appear in Proc. 34th int. Symposium on Computational Geometry (SoCG 2018). Extended version to appear in Journal of Computational Geometry.   
E. Aamari, J. Kim, F. Chazal, B. Michel, A. Rinaldo, L. Wasserman. Estimating the Reach of a Manifold, Electronic Journal of Statistics, 2019.   
H. Anai, F. Chazal, M. Glisse, Y. Ike, H. Inakoshi, R. Tinarrage, Y. Umeda, DTM-based filtrations, in to appear in Abel Symp. Proc. 2019. Extended version of a paper in Symp. Comp. Geom 2019 (SoCG 2019).   
F. Chazal, B. T. Fasy, F. Lecci, B. Michel, A. Rinaldo, L. Wasserman. Robust Topological Inference: Distance To a Measure and Kernel Distance arXiv:1412.7197. In JJournal of Machine Learning Research 18 (2018) 1-40.   
R. Huang, F. Chazal, M. Ovsjanikov. On the Stability of Functional Maps and Shape Difference Operators. Computer Graphics Forum, 37 (1), 145--158, 2018.   
F. Chazal, P. Massart, B. Michel. Rates of Convergence for Robust Geometric Inference. Electronic Journal of Statistics Volume 10, Number 2 (2016), 2243-2286.   
M. Buchet and F. Chazal and S. Y. Oudot and D. R. Sheehy. Efficient and Robust Persistent Homology for Measures. To appear in Computational Geometry: Theory and Applications, 2016..
F. Chazal, W. Crawley-Boevey, V. de Silva. The observable structure of persistence modules, in Homology, Homotopy and Applications,vol. 18, 2, p.247-265 2016.
F. Chazal, M. Glisse, C. Labruere, B. Michel. Convergence rates for persistence diagram estimation in Topological Data Analysis. In Journal of Machine Learning Research (JMLR), Vol. 16, p. 3603-3635, Dec. 2015.
F. Chazal, R. Huang, J. Sun. Gromov-Hausdorff Approximation of Filament Structure Using Reeb-type Graph. To appear in Discrete and Computational Geometry (Extended version of the SoCG 2014 version with topological guarantees), 2015.   
O. Azencot, M. Ovsjanikov, F. Chazal, M. Ben-Chen. Discrete Derivatives of Vector Fields on Surfaces An Operator Approach. ACM Transactions on Graphics (TOG), Volume 34 Issue 3, April 2015, Article No. 29.   
F. Chazal, B.T. Fasy, F. Lecci, A. Rinaldo, L. Wasserman. Stochastic Convergence of Persistence Landscapes and Silhouettes. To appear in Journal of Computational Geometry 2015 (conference version in SoCG 2014).   
F. Chazal, V. de Silva. S. Oudot. Persistence Stability for Geometric Complexes. To appear in Geometriae Dedicata (online First, December 2013), see arXiv:1207.3885v1 [math.AT].   
F. Chazal, B. Fasy, F. Lecci, A. Rinaldo, A. Singh, L. Wasserman. On the Bootstrap for Persistence Diagrams and Landscapes. Modeling and Analysis of Information Systems, 20:6 (2013), 96--105.   
F. Chazal, L. J. Guibas, S. Y. Oudot, P. Skraba. Persistence-Based Clustering in Riemannian Manifolds. Proc. 27th Annual ACM Symposium on Computational Geometry, pages 97-106, 2011. Full version in Journal of the ACM, volume 60, issue 6, article 41.   
M. Ovsjanikov, M. Ben-Chen, F. Chazal, L. Guibas. Analysis and Visualization of Maps Between Shapes. In Computer Graphics Forum (2013).   
M. Aanjaneya, F. Chazal, D. Chen, M. Glisse, L. J. Guibas, D. Morozov. Metric Graph Reconstruction from Noisy Data. In Intern. Journal on Computational Geometry and Applications, vol 22, No 4, p.305-325 (2012).   
F. Chazal, A. Patel, P. Skraba. Computing Well Diagrams for Vector Fields on Rn. In Applied Mathematics Letters, 2012.   
C. Caillerie, F. Chazal, J. Dedecker, B. Michel. Deconvolution for the Wasserstein metric and geometric inference. In Electronic Journal of Statistics, vol. 5, p.1394-1423, 2011.   
F. Chazal, D. Cohen-Steiner, Q. Mérigot. Geometric Inference for Probability Measures. In Journal on Foundations of Computational Mathematics, 2011, volume 11, number 6.   
G. Biau, F. Chazal, D. Cohen-Steiner, L. Devroye, C. Rodrigues. A Weighted k-Nearest Neighbor Density Estimate for Geometric Inference. In Electronic Journal of Statistics, vol. 5, p. 204-237, 2011.   
F. Chazal, L. J. Guibas, S. Oudot, P. Skraba. Scalar Field Analysis over Point Cloud Data. In Discrete and Computational Geometry, Vol. 46, 4, pp.743-775, 2011.   
F. Chazal, D. Cohen-Steiner, Q. Mérigot. Boundary Measures for Geometric Inference. In Journal on Foundations of Computational Mathematics, 2009, Volume 10, Issue 2, p.221-240, 2010.   
F. Chazal, D. Cohen-Steiner, L. J. Guibas, F. M\'emoli, S. Oudot. Gromov-Hausdorff Stable Signatures for Shapes using Persistence. In Computer Graphics Forum (proc. SGP 2009), pp. 1393-1403, 2009.   
F. Chazal, D. Cohen-Steiner, A. Lieutier, B. Thibert. Stability of Curvature Measures. In Computer Graphics Forum (proc. SGP 2009), pp. 1485-1496, 2009. Extended version with complete proofs   
F. Chazal, A. Lieutier, N. Montana Discrete Critical Values: a General Framework for Silhouettes Computations. In Computer Graphics Forum (proc. SGP 2009), pp. 1509-1518, 2009.   
F. Chazal, D. Cohen-Steiner, A. Lieutier. Normal Cone Approximation and Offset Shape Isotopy. In Comp. Geom: Theory and Applications, vol 42, 6-7, pp. 566-581, 2009.   
F. Chazal, A. Lieutier, J. Rossignac, B. Whited. Ball map: median projection map between compatible surfaces. In Int. Journal of Computational Geometry and Applications, volume 20, issue 3, p.285-306, 2010.   
F. Chazal, A. Lieutier. Smooth Manifold Reconstruction from Noisy and Non Uniform Approximation with Guarantees. In Comp. Geom: Theory and Applications, vol 40(2008) pp 156-170.   
F. Chazal, D. Cohen-Steiner, A. Lieutier. A Sampling Theory for Compact Sets in Euclidean Spaces. In Discrete and Computational Geometry, Vol 41, 3, (2009).   
F. Chazal, A. Lieutier. Stability and computation of topological invariants of solids in R^n. In Discrete and Computational Geometry, Volume 37, Number 4, pp. 601-617, May 2007.   
F. Chazal, A. Lieutier, J. Rossignac. Normal-map between normal-compatible manifolds. In Int. Journal of Computational Geometry and Applications, volume 17, Issue 5, p.403-421, 2007.   
F. Chazal, A. Lieutier. The $\lambda$-medial axis. In Graphical Models, Volume 67, Issue 4 (2005), pp. 304-331 (Graphical Models Second Top-Cited Article 2005-2010).   
F. Chazal, D. Cohen-Steiner. A condition for isotopic approximation. In Graphical Models, Volume 67, Issue 5 (2005), pp. 390-404.   
F. Chazal, V. Maume-Deschamps. Statistical properties of general Markov dynamical sources: applications to information theory. In Discrete Mathematics and Theoretical Computer Science, Vol. 6, 2 (2004), pp. 283-314.   
F. Chazal, R. Soufflet. Stability and finiteness properties of medial axis and skeleton. In Journal of Dynamical and Control Systems, vol. 10, No. 2, p. 149-170, 2004.   
F. Chazal, V. Maume-Deschamps et B. Vall\'ee. Erratum to ``Dynamical sources in information theory : fundamentals intervals and word prefixes'' by B. Vall\'ee. In Algorithmica, vol. 38, No 4, 2004, pp 591-596.   
F. Chazal, J.-M. Lion. Volumes transverses aux feuilletages définissables dans des structures o-minimales. In Publicacions Matematiques vol.47, num 2, p.441-450 (2003).   
F. Chazal. Un théoreme de prolongement d'applications méromorphes In Math. Ann. 320, p285-297 (2001).   
F. Chazal J.-M. Lion. Une propriété des solutions non spiralantes d'équations différentielles analytiques du plan. In C.R. Acad. Sci. Paris, t.327, S\'erie I, p.451-454 (1998).   
F. Chazal. Structure locale et globale des feuilletages de Rolle, un théoreme de fibration. In Ann. Inst. Fourier, Grenoble 48, 2, p.553-592 (1998).   
F. Chazal. Sur les feuilletages algébriques de Rolle. In Comment. Math. Helv. 72, 3, (1997), p.411-425.   
F. Chazal. Un théoreme de fibration pour les feuilletages algébriques de codimension un de R^n. In C.R. Acad. Sci. Paris, t.321, S\'erie I, p.327-330 (1995).   

Books chapters, course notes in conferences

Boissonnat, JD., Chazal, F., Michel, B. Topological Data Analysis. In: Günther, M., Schilders, W. (eds) Novel Mathematics Inspired by Industrial Challenges. Mathematics in Industry, vol 38. Springer, 2022.   
F. Chazal, D. Cohen-Steiner, A. Lieutier, Q. Mérigot, B. Thibert. Inference of curvature using tubular neighborhoods. in Modern Approaches to Discrete Curvature; Lecture Notes in Mathematics 2184, Springer, 2017.   
M. Ovsjanikov, E. Corman, M. Bronstein, E. Rodolà, M. Ben-Chen, L. Guibas, F. Chazal, A. Bronstein. Computing and Processing Correspondences with Functional Maps, Proc. SIGGRAPH Asia Courses 2016.   
F. Chazal, High-Dimensional Topological Data Analysis. To appear in the 3rd edition of the Handbook of Discrete and Computational Geometry.
F. Cazals, F. Chazal, J. Giesen. Spectral Techniques to Explore Point Clouds in Euclidean Spaces, with Applications in Structural Biology. In IMA Volume 151: Nonlinear Computational Geometry edited by Ioannis Z. Emiris, Frank Sottile, and Thorsten Theobald, 2009.   
F. Chazal, D. Cohen-Steiner. Geometric Inference. To appear as a chapter in a book entitled "Tesselations in the Sciences".   

Conference proceedings

Mathieu Carriere, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan. Optimizing persistent homology based functions. In proc of ICML 2021.    T. Lacombe, M. Carrière, F. Chazal, Y. Ike, M. Glisse, Y. Umeda. Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs}. To appear in Proc. IJCAI 2021.    F. Chazal, C. Levrard, Y. Ike, M. Royer, Y. Umeda. ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning. AISTATS 2021.   
Kwangho Kim, Jisu Kim, Manzil Zaheer, Joon Sik Kim, Frederic Chazal, Larry Wasserman. Efficient Topological Layer based on Persistent Landscapes. NeurIPS 2020. ,   
M. Dindin, Y. Umeda, F. Chazal. Topological Data Analysis for Arrhythmia Detection through Modular Neural Networks. To appear in Proc. 33rd Canadian Conference on Artificial Intelligence, 2020.   
Jisu Kim, Jaehyeok Shin, Frederic Chazal, Alessandro Rinaldo and Larry Wasserman. Homotopy Reconstruction via the Cech Complex and the Rips Complex. To appear in Proc Symposium on Comp. Geom. 2020 (SoCG 2020).   
Q. Mérigot, A. Delalande, F. Chazal. Quantitative stability of optimal transport maps and linearization of the 2-wasserstein space. To appear in AISTATS 2020.   
M. Carriere, F. Chazal, Y. Ike, T. Lacombe, M. Royer, Y. Umeda, PersLay: A Simple and Versatile Neural Network Layer for Persistence Diagrams, preprint, April (initial version) and June (updated version) 2019. To appear in AISTATS 2020   
B. Beaufils, F. Chazal, M. Grelet, B. Michel. Robust pedestrian trajectory reconstruction from inertial sensor. IPIN 2019 - 10th International Conference on Indoor Positioning and Indoor Navigation.   
H. Anai, F. Chazal, M. Glisse, Y. Ike, H. Inakoshi, R. Tinarrage, Y. Umeda, DTM-based filtrations, in proc Symp. Comp. Geom 2019 (SoCG 2019). Extended version to appear in Abel Symp. Proc. 2019.   
B. Beaufils, F. Chazal, M. Grelet, B. Michel. Activity recognition from stride detection: a machine learning approach based on geometric patterns and trajectory reconstruction. IPIN 2018 - 9th International Conference on Indoor Positioning and Indoor Navigation.   
V. Divol, F. Chazal. The density of expected persistence diagrams and its kernel based estimation. Proc. 34th int. Symposium on Computational Geometry (SoCG 2018).   
B. Beaufils, F. Chazal, M. Grelet, B. Michel. Stride detection for pedestrian trajectory reconstruction: a machine learning approach based on geometric patterns. To appear in Proc. of the Eighth International Conference on Indoor Positioning and Indoor Navigation 2017 (IPIN 2017).   
F. Chazal, I. Giulini, B. Michel. Data driven estimation of Laplace-Beltrami operator}. The Thirtieth Annual Conference on Neural Information Processing Systems (NIPS 2016).   
T. Bonis, M. Ovsjanikov, S. Oudot, F. Chazal. Persistence-based Pooling for Shape Pose Recognition. 6th International Workshop on Computational Topology in Image Context (CTIC 2016), June 2016, Marseille, France.
F. Chazal, B.T. Fasy, F. Lecci, B. Michel, A. Rinaldo, L. Wasserman. Subsampling Methods for Persistent Homology. In proc. International Conference on Machine Learning (ICML 2015).   
M. Buchet and F. Chazal and T. Dey and F. Fan and S. Oudot and Y. Wang. Topological Analysis of Scalar Fields with Outliers. arXiv:1412.1680 [cs.CG]. To appear in 31st International Symposium on Computational Geometry (SOCG 2015).   
M. Buchet and F. Chazal and S. Y. Oudot and D. R. Sheehy. Efficient and Robust Persistent Homology for Measures. In ACM-SIAM Symposium on Discrete Algorithms 2015 (SODA 2015). Full version available in arXiv:1306.0039 [cs.CG].   
C. Li, M. Ovsjanikov, F. Chazal. Persistence-based Structural Recognition. In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014).
F. Chazal, M. Glisse, C. Labruere, B. Michel. Convergence rates for persistence diagram estimation in Topological Data Analysis. In proc. International Conference on Machine Learning (ICML 2014).
F. Chazal, J. Sun. Gromov-Hausdorff Approximation of Filament Structure Using Reeb-type Graph. In proc. ACM Symposium of Computational Geometry 2014.   
F. Chazal, B.T. Fasy, F. Lecci, A. Rinaldo, L. Wasserman. Stochastic Convergence of Persistence Landscapes and Silhouettes. In proc. ACM Symposium of Computational Geometry 2014.   
O. Azencot, M. Ben-Chen, F. Chazal, M. Ovsjanikov. An Operator Approach to Tangent Vector Field Processing. In Computer Graphics Forum (proc. SGP 2013).
R. Rustamov, M. Ovsjanikov, O. Azencot, M. Ben-Chen, F. Chazal, L. Guibas Map-Based Exploration of Intrinsic Shape Differences and Variability. In SIGGRAPH 2013.
F. Chazal, D. Chen, L. Guibas, X. Jiang, C. Sommer. Data-Driven Trajectory Smoothing. In Proc. ACM SIGSPATIAL GIS 2011.   
F. Chazal, L. J. Guibas, S. Oudot, P. Skraba. Persistent-Based Clustering in Riemannian Manifolds. In proc. ACM Symposium of Computational Geometry 2011.   
M. Aanjaneya, F. Chazal, D. Chen, M. Glisse, L. J. Guibas, D. Morozov. Metric Graph Reconstruction from Noisy Data. In proc. ACM Symposium of Computational Geometry 2011.   
F. Chazal, D. Cohen-Steiner, Q. M\'erigot. Geometric Inference Using Distance-like Functions. In 9th International Conference on Sampling Theory and Applications (SampTA 2011).   
P. Skraba, M. Ovsjanikov, F. Chazal, L. Guibas. Persistence-Based Segmentation of Deformable Shapes. In Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), Proc. CVPR 2010 (Best Paper Award).   
F. Chazal, D. Cohen-Steiner, M. Glisse, L. J. Guibas, S. Oudot. Proximity of persistence modules and their diagrams. In proc. 2009 ACM Symposium of Computational Geometry.   
F. Chazal, L. J. Guibas, S. Oudot, P. Skraba. Analysis of Scalar Fields over Point Cloud Data. In proc ACM Symposium on discrete algorithms 2009 (SODA'09).   
F. Chazal, S. Oudot. Towards Persistence-Based Reconstruction in Euclidean Spaces. In Proc. ACM Symp. of Computational Geometry 2008.   
F. Chazal, D. Cohen-Steiner, A. Lieutier, B. Thibert. Shape Smoothing using Double Offsets. In ACM solid and Physical Modeling 2007.   
F. Chazal, D. Cohen-Steiner, A. Lieutier. A Sampling Theory for Compacts in Euclidean Spaces. In proc. ACM Symp. of Computational Geometry 2006.   
F. Chazal, A. Lieutier. Topology guaranteeing manifold reconstruction using distance function to noisy data. In proc. ACM Symp. of Computational Geometry 2006.   
F. Chazal, A. Lieutier. Weak feature size and persistent homology: computing homology of solids in R^n from noisy data samples. In proc. ACM Symp. of Computational Geometry 2005.   
F. Chazal, A. Lieutier, J. Rossignac. Projection-Homeomorphic Surfaces In proc. ACM Symp. on Solid and Physical Modeling 2005.   
F. Chazal, D. Cohen-Steiner. A condition for isotopic approximation. In proc. ACM Symp. of Solid Modeling and Applications 2004.   
F. Chazal, A. Lieutier. Stability and homotopy of a subset of the medial axis. In proc. ACM Symp. of Solid Modeling and Applications 2004.   
F. Cazals, F. Chazal et T. Lewiner. Molecular Shape Analysis based upon the Morse-Smale Complex and the Connolly Function. In Proceedings of the 2003 ACM Symposium on Computational Geometry p.351-360.   

Patents

M. Dindin, Y. Umeda and F. Chazal, Computer-readable recording medium, abnormality determination method, and abnormality determination device, Aug. 2019.   
F. Chazal, A. Lieutier, N. Montana. Computer-implemented method of computing, in a computer aided design system, of a boundary of a modeled object. US Patent US 8,280,698 B2, filed, Oct. 2, 2012.   
F. Chazal, A. Lieutier, N. Montana. Computing of a resulting closed triangulated polyhedral surface from a first dans a second modeled objects. US Patent US 2011/0295564 A1, filed, May 19, 2011.   

Research reports

F. Chazal, C. Levrard, M. Royer Topological Analysis for Detecting Anomalies (TADA) in Time Series arXiv:2406.06168, 2024.   
S. Gaucher, G. Blanchard, F. Chazal. Supervised Contamination Detection, with Flow Cytometry Application. arXiv:2404.06093, 2024.   
T. de Surrel, F. Hensel, M. Carrière, T. Lacombe, Y. Ike, H. Kurihara, M. Glisse, F. Chazal RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. Feb. 2022.   
H. Anai, F. Chazal, M. Glisse, Y. Ike, H. Inakoshi, R. Tinarrage, Y. Umeda, DTM-based filtrations, Nov. 2018, submitted.   
F. Chazal, P. Massart, B. Michel. Rates of Convergence for Robust Geometric Inference arXiv:1505.07602   
F. Chazal, B. T. Fasy, F. Lecci, B. Michel, A. Rinaldo, L. Wasserman. Robust Topological Inference: Distance To a Measure and Kernel Distance arXiv:1412.7197   
F. Chazal, B.T. Fasy, F. Lecci, B. Michel, A. Rinaldo, L. Wasserman. Subsampling Methods for Persistent Homology. See arXiv:1406.1901
F. Chazal, W. Crawley-Boevey, V. de Silva. The observable structure of persistence modules, see arXiv:1405.5644 [math.AT].
M. Buchet, F. Chazal, T. Dey, F. Fan, S. Oudot, Y. Wang. Topological analysis of scalar field with outliers. Submitted   
F. Chazal, B. Fasy, F. Lecci, A. Rinaldo, A. Singh, L. Wasserman. On the Bootstrap for Persistence Diagrams and Landscapes. See arXiv:1311.0376, Nov. 2013.
F. Chazal, V. de Silva, M. Glisse, S. Oudot. The Structure and Stability of Persistence Modules. Monograph under review, see arXiv:1207.3674v1 [math.AT].
F. Chazal, D. Cohen-Steiner, A. Lieutier, B. Thibert. Stability of Curvature Measures. INRIA Research Report RR-6756, December 2008 (short version published in Comp. Graphic Forum, proc. SGP 2009).

Misc.

J.-D. Boissonnat, F. Chazal, M. Yvinec. Geometric Inference. book in preparation
F. Chazal, S. Oudot. Interleaved Filtrations: Theory and Applications in Point Cloud Data Analysis. In Lecture Notes in Computer Science 8085, p.587-592, 2013.
C. Caillerie, F. Chazal, J. Dedeker, B. Michel. Deconvolution for the Wasserstein Metric and Geometric Inference. In Lecture Notes in Computer Science 8085, p.561-568, 2013.
F. Chazal. Trouver la geometrie dans une meule de points. Images des Math\'ematiques, CNRS, 2012.
F. Chazal, Quelques contributions en approximation geometrique et topologique, en analyse dynamique d'algorithmes et a l'etude des feuilletages non spiralants. Memoire d'habilitation a diriger des recherches (2005).
F. Chazal, V. Maume-Deschamps, B. Vall\'ee. Notes du cours de B. Vallee, ALEA 2002~: Systemes dynamiques et algorithmique. Algorithms Seminar 2001-2002, F. Chyzak (ed.), INRIA, 2003, p.121-150.
F. Chazal. Foliaciones analiticas de Rolle : estructura global y local. Revista del Seminario Iberoamericano de Matematicas, Vol. II, Fasc. 1 (1998).
F. Chazal. Estructura de las foliaciones algebraicas de Rolle. Revista del Seminario Iberoamericano de Matematicas, Fasc. 6 (1997).
F. Chazal. Sur les feuilletages de Rolle. These de l'Universite de Bourgogne, Novembre 1997.
L. van den Dries. Theorie des modeles elementaire. Notes d'un cours donne a Dijon en juin 96, redigees par F. Chazal.