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Publications of Nina Miolane

Thesis

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


Articles in journal, book chapters

  1. 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]


  2. 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]


  3. 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]


  4. 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]


  5. 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, consistency, shape, bias. [bibtex-entry]


  6. 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): Image processing, neurogeometry, sub-Riemannian geometry. [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): pseudo-Riemannian, Statistics, computational anatomy, Lie group, exponential barycenter, metric, manifold. [bibtex-entry]


Miscellaneous

  1. 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]


  2. 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]


  3. 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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