Nina Miolane
Nina Miolane
Assistant Professor at UC Santa Barbara
Verified email at - Homepage
Cited by
Cited by
Geomstats: a Python package for Riemannian geometry in machine learning
N Miolane, N Guigui, A Le Brigant, J Mathe, B Hou, Y Thanwerdas, ...
Journal of Machine Learning Research 21 (223), 1-9, 2020
Computing CNN loss and gradients for pose estimation with Riemannian geometry
B Hou, N Miolane, B Khanal, MCH Lee, A Alansary, S McDonagh, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
PVNet: A LRCN architecture for spatio-temporal photovoltaic PowerForecasting from numerical weather prediction
J Mathe, N Miolane, N Sebastien, J Lequeux
arXiv preprint arXiv:1902.01453, 2019
Deep generative modeling for volume reconstruction in cryo-electron microscopy
C Donnat, A Levy, F Poitevin, ED Zhong, N Miolane
Journal of structural biology 214 (4), 107920, 2022
Cryoai: Amortized inference of poses for ab initio reconstruction of 3d molecular volumes from real cryo-em images
A Levy, F Poitevin, J Martel, Y Nashed, A Peck, N Miolane, D Ratner, ...
European Conference on Computer Vision, 540-557, 2022
Estimation of orientation and camera parameters from cryo-electron microscopy images with variational autoencoders and generative adversarial networks
N Miolane, F Poitevin, YT Li, S Holmes
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Topological deep learning: Going beyond graph data
M Hajij, G Zamzmi, T Papamarkou, N Miolane, A Guzmán-Sáenz, ...
arXiv preprint arXiv:2206.00606, 2022
Template shape estimation: correcting an asymptotic bias
N Miolane, S Holmes, X Pennec
SIAM Journal on Imaging Sciences 10 (2), 808-844, 2017
Computing bi-invariant pseudo-metrics on lie groups for consistent statistics
N Miolane, X Pennec
Entropy 17 (4), 1850-1881, 2015
Architectures of topological deep learning: A survey on topological neural networks
M Papillon, S Sanborn, M Hajij, N Miolane
arXiv preprint arXiv:2304.10031, 2023
ICLR 2021 challenge for computational geometry & topology: Design and results
N Miolane, M Caorsi, U Lupo, M Guerard, N Guigui, J Mathe, Y Cabanes, ...
arXiv preprint arXiv:2108.09810, 2021
Learning weighted submanifolds with variational autoencoders and riemannian variational autoencoders
N Miolane, S Holmes
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
Introduction to riemannian geometry and geometric statistics: from basic theory to implementation with geomstats
N Guigui, N Miolane, X Pennec
Foundations and Trends® in Machine Learning 16 (3), 329-493, 2023
Introduction to geometric learning in Python with Geomstats
N Miolane, N Guigui, H Zaatiti, C Shewmake, H Hajri, D Brooks, ...
SciPy 2020-19th Python in Science Conference, 48-57, 2020
Biased estimators on quotient spaces
N Miolane, X Pennec
International Conference on Geometric Science of Information, 130-139, 2015
Deep pose estimation for image-based registration
B Hou, N Miolane, B Khanal, M Lee, A Alansary, S McDonagh, J Hajnal, ...
A Bayesian hierarchical network for combining heterogeneous data sources in medical diagnoses
C Donnat, N Miolane, F Bunbury, J Kreindler
Machine Learning for Health, 53-84, 2020
A survey of mathematical structures for extending 2D neurogeometry to 3D image processing
N Miolane, X Pennec
Medical Computer Vision: Algorithms for Big Data: International Workshop …, 2016
Heterogeneous reconstruction of deformable atomic models in Cryo-EM
Y Nashed, A Peck, J Martel, A Levy, B Koo, G Wetzstein, N Miolane, ...
arXiv preprint arXiv:2209.15121, 2022
Analyse biométrique de l’anneau pelvien en 3 dimensions–à propos de 100 scanners
H Darmanté, B Bugnas, RB De Dompsure, L Barresi, N Miolane, ...
Revue de Chirurgie Orthopédique et Traumatologique 100 (7), S241, 2014
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