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Publications of Nina Miolane

Thesis

  1. Nina Miolane. Geometric statistics for computational anatomy. Theses, COMUE Université Côte d'Azur (2015 - 2019), December 2016. Keyword(s): Statistics, Geometry, Medical imaging, Anatomy, Statistiques, Géométrie, Imagerie médicale, Anatomie. [bibtex-entry]


Articles in journal, book chapters

  1. Nicolas Guigui, Nina Miolane, and Xavier Pennec. Introduction to Riemannian Geometry and Geometric Statistics: from basic theory to implementation with Geomstats. Foundations and Trends in Machine Learning, 16(3):329-493, February 2023. Keyword(s): Riemannian Geometry, Geometric Statistics, Python Library. [bibtex-entry]


  2. Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Soren Hauberg, Dmitriy Nielsen, Stefan Sommer, David Klindt, Erik Hermansen, Melvin Vaupel, Benjamin Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'Er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, and Nina Miolane. ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. Proceedings of Machine Learning Research, 196:269-276, November 2022. [bibtex-entry]


  3. 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]


  4. Nina Miolane, Loïc Devilliers, and Xavier Pennec. Bias on estimation in quotient space and correction methods: Applications to statistics on organ shapes. In Riemannian Geometric Statistics in Medical Image Analysis, number Chap. 9, pages 343-376. Elsevier, 2020. [bibtex-entry]


  5. Nina Miolane, Susan Holmes, and Xavier Pennec. Topologically constrained template estimation via Morse-Smale complexes controls its statistical consistency. SIAM Journal on Applied Algebra and Geometry, 2(2):348-375, 2018. [bibtex-entry]


  6. Nina Miolane. Les maths de l'espace-temps qui décrivent et dépassent le cerveau. Interstices, February 2017. Keyword(s): anatomie cérébrale, anatomie numérique, modélisation mathématique, géométrie riemannienne, cortex visuel, neuroimagerie, image 3D, perception visuelle. [bibtex-entry]


  7. Nina Miolane, Susan Holmes, and Xavier Pennec. Template Shape Estimation: Correcting an Asymptotic Bias. SIAM Journal on Imaging Sciences, 10(2):808 - 844, 2017. Keyword(s): geometry, quotient space, manifold, template, bias, shape, consistency. [bibtex-entry]


  8. Nina Miolane and Xavier Pennec. Computing Bi-Invariant Pseudo-Metrics on Lie Groups for Consistent Statistics. Entropy, 17(4):1850-1881, April 2015. [bibtex-entry]


Conference articles

  1. 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]


  2. Nina Miolane and Xavier Pennec. A survey of mathematical structures for extending 2D neurogeometry to 3D image processing. In MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data. MCV 2015., volume 9601 of LNCS, Munich, Germany, pages 155-167, October 2015. Keyword(s): sub-Riemannian geometry, Image processing, neurogeometry. [bibtex-entry]


  3. Nina Miolane and Xavier Pennec. Biased estimators on Quotient spaces. In Geometric Science of Information. Second International Conference, GSI 2015., volume 9389 of Lecture notes in computer science (LNCS), Palaiseau, France, pages 130-139, October 2015. Springer. [bibtex-entry]


  4. Hugo Darmanté, Benoit Bugnas, Regis Bernard De Dompsure, Laurent Barresi, Nina Miolane, Xavier Pennec, Fernand de Peretti, and Nicolas Bronsard. Analyse biométrique de l'anneau pelvien en 3 dimensions - à propos de 100 scanners. In 89e Réunion annuelle de la SOFCOT, volume 100 of Revue de Chirurgie Orthopédique et Traumatologique, Paris, France, November 2014. [bibtex-entry]


  5. Nina Miolane and Xavier Pennec. Statistics on Lie groups : a need to go beyond the pseudo-Riemannian framework. In Bayesian inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2014), volume 1641 of AIP Conference Proceedings, Amboise, France, pages 59-66, September 2014. AIP Proceedings. Keyword(s): manifold, metric, exponential barycenter, Lie group, computational anatomy, Statistics, pseudo-Riemannian. [bibtex-entry]


Miscellaneous

  1. Anna Calissano, Luìs F Pereira, Jonas Lueg, and Nina Miolane. On the Implementation of Geodesic Metric Spaces. Note: Working paper or preprint, June 2024. Keyword(s): geodesic metric spaces, BHV space, tree-valued data, graph-valued data, geometric data analysis. [bibtex-entry]


  2. 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]


  3. Nina Miolane, Johan Mathe, Claire Donnat, Mikael Jorda, and Xavier Pennec. geomstats: a Python Package for Riemannian Geometry in Machine Learning. Note: Preprint NIPS2018, January 2019. [bibtex-entry]


  4. Nina Miolane, Xavier Pennec, and Susan Holmes. Towards a unified bayesian geometric framework for template estimation in Computational Anatomy. International Society of Bayesian Analysis: World Meeting, June 2016. Note: Poster. Keyword(s): template, shape, manifold, estimation, medical imaging. [bibtex-entry]


  5. Nina Miolane. Defining a mean on Lie group. Master's thesis, Imperial College London, September 2013. Keyword(s): Lie group. [bibtex-entry]



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