| 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 | 153* | 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 | 74* | 2022 |
| Architectures of topological deep learning: A survey of message-passing topological neural networks M Papillon, S Sanborn, M Hajij, N Miolane arXiv preprint arXiv:2304.10031, 2023 | 56 | 2023 |
| 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 | 44 | 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 | 44 | 2022 |
| 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 | 39 | 2019 |
| 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 | 38 | 2018 |
| Position: Topological deep learning is the new frontier for relational learning T Papamarkou, T Birdal, M Bronstein, G Carlsson, J Curry, Y Gao, M Hajij, ... arXiv preprint arXiv:2402.08871, 2024 | 37 | 2024 |
| 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 | 28 | 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 | 22 | 2023 |
| Computing bi-invariant pseudo-metrics on Lie groups for consistent statistics N Miolane, X Pennec Entropy 17 (4), 1850-1881, 2015 | 22 | 2015 |
| Template shape estimation: correcting an asymptotic bias N Miolane, S Holmes, X Pennec SIAM Journal on Imaging Sciences 10 (2), 808-844, 2017 | 20 | 2017 |
| 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 | 18 | 2020 |
| Position paper: Challenges and opportunities in topological deep learning T Papamarkou, T Birdal, M Bronstein, G Carlsson, J Curry, Y Gao, M Hajij, ... arXiv preprint arXiv:2402.08871 24, 25, 2024 | 16 | 2024 |
| 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 | 16 | 2021 |
| 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 | 13 | 2020 |
| 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 | 10 | 2022 |
| Deep pose estimation for image-based registration B Hou, N Miolane, B Khanal, M Lee, A Alansary, S McDonagh, J Hajnal, ... | 10 | 2018 |
| Biased estimators on quotient spaces N Miolane, X Pennec International Conference on Geometric Science of Information, 130-139, 2015 | 10 | 2015 |
| Topological deep learning: Going beyond graph data, may 2023 M Hajij, G Zamzmi, T Papamarkou, N Miolane, A Guzmán-Sáenz, ... arXiv preprint arXiv:2206.00606, 0 | 10 | |
Xavier PennecSenior Research Scientist (Directeur de Recherche), INRIA, Epione teamVerified email at inria.fr
