Publications of Nicolas Guigui

1. Nicolas Guigui, Nina Miolane, and Xavier Pennec. Introduction to Riemannian Geometry and Geometric Statistics: from basic theory to implementation with Geomstats, volume 16 of Foundations and Trends® in Machine Learning. Know Publishers, February 2023. Keyword(s): Riemannian Geometry, Geometric Statistics, Python Library. [bibtex-entry]

1. Nicolas Guigui. Computational methods for statistical estimation on Riemannian manifolds and application to the study of the cardiac deformations. Theses, Université Côte d'Azur, November 2021. Keyword(s): Differential geometry, Computational anatomy, Geometric statistics, Géométrie différentielle, Anatomie computationnelle, Statistiques géométriques. [bibtex-entry]

1. Nicolas Guigui and Xavier Pennec. Numerical Accuracy of Ladder Schemes for Parallel Transport on Manifolds. Foundations of Computational Mathematics, 22:757-790, June 2022. [bibtex-entry]



2. Nicolas Guigui and Xavier Pennec. Parallel transport, a central tool in geometric statistics for computational anatomy: Application to cardiac motion modeling. In Frank Nielsen, Arni S.R. Srinivasa Rao, and C.R. Rao, editors, Geometry and Statistics, volume 46 of Handbook of Statistics, pages 285-326. Elsevier, May 2022. Keyword(s): Parallel transport, longitudinal studies, mean trajectory, cardiac motion analysis, Schild's ladder, pole ladder, Riemannian manifolds. [bibtex-entry]



3. Alice Le Brigant, Nicolas Guigui, Sana Rebbah, and Stéphane Puechmorel. Classifying histograms of medical data using information geometry of beta distributions. IFAC-PapersOnLine, June 2021. Keyword(s): histogram analysis, clustering, medical imaging, Information geometry, classification. [bibtex-entry]



4. Emmanuel Chevallier and Nicolas Guigui. A Bi-Invariant Statistical Model Parametrized by Mean and Covariance on Rigid Motions. Entropy, 22(4):432, 2020. Keyword(s): moment-matching estimator, Euclidean groups, density estimation, wrapped distributions, rigid motions, sampling, differential of the exponential. [bibtex-entry]



5. Nina Miolane, Nicolas Guigui, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Daniel Brooks, Bernhard Kainz, Claire Donnat, Susan Holmes, and Xavier Pennec. Geomstats: A Python Package for Riemannian Geometry in Machine Learning. Journal of Machine Learning Research, 21(223):1-9, December 2020. Keyword(s): differential geometry, Riemannian geometry, statistics, machine learning, manifold. [bibtex-entry]

1. Maxime Di Folco, Nicolas Guigui, Patrick Clarysse, Pamela Moceri, and Nicolas Duchateau. Investigation of the impact of normalization on the study of interactions between myocardial shape and deformation. In FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart, volume 12738 of Lectune notes in computer science (LNCS), Stanford, United States, pages 223-231, June 2021. Springer. Keyword(s): Cardiac imaging, manifold learning, myocardial strain, heart shape. [bibtex-entry]



2. Nicolas Guigui, Elodie Maignant, Alain Trouvé, and Xavier Pennec. Parallel Transport on Kendall Shape Spaces. In GSI 2021 - 5th conference on Geometric Science of Information, volume 12829 of Lecture Notes in Computer Science, Paris, France, pages 103-110, July 2021. Springer. [bibtex-entry]



3. Nicolas Guigui, Pamela Moceri, Maxime Sermesant, and Xavier Pennec. Cardiac Motion Modeling with Parallel Transport and Shape Splines. In ISBI 2021 - 18th IEEE International Symposium on Biomedical Imaging, IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021, Nice, France, pages pp. 1394-1397, April 2021. IEEE. Keyword(s): LDDMM, Cardiac Modelling, Shape Analysis. [bibtex-entry]



4. Nicolas Guigui and Xavier Pennec. A reduced parallel transport equation on Lie Groups with a left-invariant metric. In GSI 2021 - 5th conference on Geometric Science of Information, volume 12829 of Lecture Notes in Computer Science, Paris, France, pages 119-126, July 2021. Springer, Cham. [bibtex-entry]



5. Emmanuel Chevallier and Nicolas Guigui. Wrapped statistical models on manifolds: motivations, the case SE(n), and generalization to symmetric spaces. In Joint Structures and Common Foundations of Statistical Physics, Information Geometry and Inference for Learning, Les Houches, France, July 2020. Keyword(s): Non-Euclidean statistics, wrapped distributions, exponential map, moment matching estimator. [bibtex-entry]



6. Nina Miolane, Nicolas Guigui, Hadi Zaatiti, Christian Shewmake, Hatem Hajri, Daniel Brooks, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Yann Cabanes, Thomas Gerald, Paul Chauchat, Bernhard Kainz, Claire Donnat, Susan Holmes, and Xavier Pennec. Introduction to Geometric Learning in Python with Geomstats. In Meghann Agarwal, Chris Calloway, Dillon Niederhut, and David Shupe, editors, SciPy 2020 - 19th Python in Science Conference, Austin, Texas, United States, pages 48-57, July 2020. Keyword(s): Index Terms-differential geometry, statistics, manifold, machine learning. [bibtex-entry]



7. Nicolas Guigui, Shuman Jia, Maxime Sermesant, and Xavier Pennec. Symmetric Algorithmic Components for Shape Analysis with Diffeomorphisms. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 759-768, August 2019. F. Nielsen and F. Barbaresco, Springer. Keyword(s): Symmetric Spaces, Parallel Transport, Shape Registration. [bibtex-entry]

1. Nina Miolane, Matteo Caorsi, Umberto Lupo, Marius Guerard, Nicolas Guigui, Johan Mathe, Yann Cabanes, Wojciech Reise, Thomas Davies, António Leitão, Somesh Mohapatra, Saiteja Utpala, Shailja Shailja, Gabriele Corso, Guoxi Liu, Federico Iuricich, Andrei Manolache, Mihaela Nistor, Matei Bejan, Armand Mihai Nicolicioiu, Bogdan-Alexandru Luchian, Mihai-Sorin Stupariu, Florent Michel, Khanh Dao Duc, Bilal Abdulrahman, Maxim Beketov, Elodie Maignant, Zhiyuan Liu, Marek Cerny, Martin Bauw, Santiago Velasco-Forero, Jesus Angulo, and Yanan Long. ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results. Note: Working paper or preprint, December 2021. [bibtex-entry]

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