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Geomstats: A Python Package for Riemannian Geometry in Machine Learning


Apr 07, 2020
Nina Miolane, Alice Le Brigant, Johan Mathe, Benjamin Hou, Nicolas Guigui, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Bernhard Kainz, Claire Donnat, Susan Holmes, Xavier Pennec


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Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders


Nov 19, 2019
Nina Miolane, Susan Holmes


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Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks


Nov 19, 2019
Nina Miolane, Frédéric Poitevin, Yee-Ting Li, Susan Holmes


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PVNet: A LRCN Architecture for Spatio-Temporal Photovoltaic PowerForecasting from Numerical Weather Prediction


Feb 04, 2019
Johan Mathe, Nina Miolane, Nicolas Sebastien, Jeremie Lequeux

* 8 pages 

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geomstats: a Python Package for Riemannian Geometry in Machine Learning


Nov 06, 2018
Nina Miolane, Johan Mathe, Claire Donnat, Mikael Jorda, Xavier Pennec

* Preprint NIPS2018 

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Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry


Jul 17, 2018
Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven McDonagh, Jo V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz


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Template shape estimation: correcting an asymptotic bias


Feb 02, 2017
Nina Miolane, Susan Holmes, Xavier Pennec


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