Nina Miolane

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 56

Top Venues

University of Côte d'Azur, France (PHD)

Education History

University of Côte d'Azur, France

PHD

Publications

Simon Mataigne, Johan Mathe, Sophia Sanborn, Christopher Hillar, Nina Miolane
The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks. CoRR (2024)
Sophia Sanborn, Johan Mathe, Mathilde Papillon, Domas Buracas, Hansen Lillemark, Christian Shewmake, Abby Bertics, Xavier Pennec, Nina Miolane
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures. CoRR (2024)
Theodore Papamarkou, Tolga Birdal, Michael Bronstein, Gunnar Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
Position Paper: Challenges and Opportunities in Topological Deep Learning. CoRR (2024)
Lev Telyatnikov, Guillermo Bernárdez, Marco Montagna, Pavlo Vasylenko, Ghada Zamzmi, Mustafa Hajij, Michael T. Schaub, Nina Miolane, Simone Scardapane, Theodore Papamarkou
TopoBenchmarkX: A Framework for Benchmarking Topological Deep Learning. CoRR (2024)
Luís F. Pereira, Alice Le Brigant, Adele Myers, Emmanuel Hartman, Amil Khan, Malik Tuerkoen, Trey Dold, Mengyang Gu, Pablo Suárez-Serrato, Nina Miolane
Learning from landmarks, curves, surfaces, and shapes in Geomstats. CoRR (2024)
Mustafa Hajij, Mathilde Papillon, Florian Frantzen, Jens Agerberg, Ibrahem AlJabea, Rubén Ballester, Claudio Battiloro, Guillermo Bernárdez, Tolga Birdal, Aiden Brent, Peter Chin, Sergio Escalera, Simone Fiorellino, Odin Hoff Gardaa, Gurusankar Gopalakrishnan, Devendra Govil, Josef Hoppe, Maneel Reddy Karri, Jude Khouja, Manuel Lecha, Neal Livesay, Jan Meißner, Soham Mukherjee, Alexander Nikitin, Theodore Papamarkou, Jaro Prílepok, Karthikeyan Natesan Ramamurthy, Paul Rosen, Aldo Guzmán-Sáenz, Alessandro Salatiello, Shreyas N. Samaga, Simone Scardapane, Michael T. Schaub, Luca Scofano, Indro Spinelli, Lev Telyatnikov, Quang Truong, Robin Walters, Maosheng Yang, Olga Zaghen, Ghada Zamzmi, Ali Zia, Nina Miolane
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains. CoRR (2024)
Rubén Ballester, Pablo Hernández-García, Mathilde Papillon, Claudio Battiloro, Nina Miolane, Tolga Birdal, Carles Casacuberta, Sergio Escalera, Mustafa Hajij
Attending to Topological Spaces: The Cellular Transformer. CoRR (2024)
Simon Mataigne, Ralf Zimmermann, Nina Miolane
An efficient algorithm for the Riemannian logarithm on the Stiefel manifold for a family of Riemannian metrics. CoRR (2024)
Bongjin Koo, Julien N. P. Martel, Ariana Peck, Axel Levy, Frédéric Poitevin, Nina Miolane
Reconstructing Heterogeneous Cryo-EM Molecular Structures by Decomposing Them into Polymer Chains. CoRR (2023)
Sophia Sanborn, Nina Miolane
A General Framework for Robust G-Invariance in G-Equivariant Networks. CoRR (2023)
Francisco Acosta, Sophia Sanborn, Khanh Dao Duc, Manu S. Madhav, Nina Miolane
Quantifying Extrinsic Curvature in Neural Manifolds. CVPR Workshops (2023)
Adele Myers, Caitlin M. Taylor, Emily G. Jacobs, Nina Miolane
Geodesic Regression Characterizes 3D Shape Changes in the Female Brain During Menstruation. CoRR (2023)
Saiteja Utpala, Praneeth Vepakomma, Nina Miolane
Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metric. Trans. Mach. Learn. Res. 2023 (2023)
Sophia Sanborn, Nina Miolane
A General Framework for Robust G-Invariance in G-Equivariant Networks. NeurIPS (2023)
Wanxin Li, Jules Mirone, Ashok Prasad, Nina Miolane, Carine Legrand, Khanh Dao Duc
Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets. Frontiers Bioinform. 3 (2023)
Christian Shewmake, Nina Miolane, Bruno A. Olshausen
Group Equivariant Sparse Coding. GSI (1) (2023)
Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML (2023)
Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
Preface. TAG-ML (2023)
David A. Klindt, Sophia Sanborn, Francisco Acosta, Frédéric Poitevin, Nina Miolane
Identifying Interpretable Visual Features in Artificial and Biological Neural Systems. CoRR (2023)
Adele Myers, Caitlin M. Taylor, Emily G. Jacobs, Nina Miolane
Geodesic Regression Characterizes 3D Shape Changes in the Female Brain During Menstruation. ICCV (Workshops) (2023)
Alice Le Brigant, Jules Deschamps, Antoine Collas, Nina Miolane
Parametric Information Geometry with the Package Geomstats. ACM Trans. Math. Softw. 49 (4) (2023)
Nicolas Guigui, Nina Miolane, Xavier Pennec
Introduction to Riemannian Geometry and Geometric Statistics: From Basic Theory to Implementation with Geomstats. Found. Trends Mach. Learn. 16 (3) (2023)
Mathilde Papillon, Sophia Sanborn, Mustafa Hajij, Nina Miolane
Architectures of Topological Deep Learning: A Survey on Topological Neural Networks. CoRR (2023)
Alice Le Brigant, Jules Deschamps, Antoine Collas, Nina Miolane
Parametric information geometry with the package Geomstats. CoRR (2022)
Mathilde Papillon, Mariel Pettee, Nina Miolane
Intentional Choreography with Semi-Supervised Recurrent VAEs. CoRR (2022)
Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf
Preface. TAG-ML (2022)
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, Søren 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, Nina Miolane
ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results. CoRR (2022)
Thibault Niederhauser, Adam Lester, Nina Miolane, Khanh Dao Duc, Manu S. Madhav
Testing geometric representation hypotheses from simulated place cell recordings. CoRR (2022)
Sophia Sanborn, Christian Shewmake, Simone Azeglio, Arianna Di Bernardo, Nina Miolane
Preface. NeurReps (2022)
Mathilde Papillon, Mariel Pettee, Nina Miolane
PirouNet: Creating Dance Through Artist-Centric Deep Learning. ArtsIT (2022)
Youssef Nashed, Ariana Peck, Julien N. P. Martel, Axel Levy, Bongjin Koo, Gordon Wetzstein, Nina Miolane, Daniel Ratner, Frédéric Poitevin
Heterogeneous reconstruction of deformable atomic models in Cryo-EM. CoRR (2022)
Claire Donnat, Axel Levy, Frédéric Poitevin, Nina Miolane
Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopy. CoRR (2022)
Nicolas Legendre, Khanh Dao Duc, Nina Miolane
Defining an action of SO(d)-rotations on images generated by projections of d-dimensional objects: Applications to pose inference with Geometric VAEs. CoRR (2022)
Adele Myers, Nina Miolane
Regression-Based Elastic Metric Learning on Shape Spaces of Elastic Curves. CoRR (2022)
Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou, Nina Miolane, Aldo Guzmán-Sáenz, Karthikeyan Natesan Ramamurthy
Higher-Order Attention Networks. CoRR (2022)
Axel Levy, Frédéric Poitevin, Julien N. P. Martel, Youssef Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, Gordon Wetzstein
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images. CoRR (2022)
Axel Levy, Frédéric Poitevin, Julien N. P. Martel, Youssef S. G. Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, Gordon Wetzstein
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images. ECCV (21) (2022)
Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane
ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. TAG-ML (2022)
Mathilde Papillon, Mariel Pettee, Nina Miolane
PirouNet: Creating Intentional Dance with Semi-Supervised Conditional Recurrent Variational Autoencoders. CoRR (2022)
Wanxin Li, Ashok Prasad, Nina Miolane, Khanh Dao Duc
Using a Riemannian Elastic Metric for Statistical Analysis of Tumor Cell Shape Heterogeneity. GSI (2) (2021)
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 Cerný, Martin Bauw, Santiago Velasco-Forero, Jesús Angulo, Yanan Long
ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results. CoRR (2021)
Faria Huq, Adrish Dey, Sahra Yusuf, Dena Bazazian, Tolga Birdal, Nina Miolane
Riemannian Functional Map Synchronization for Probabilistic Partial Correspondence in Shape Networks. CoRR (2021)
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 P. Holmes, Xavier Pennec
Introduction to Geometric Learning in Python with Geomstats. SciPy (2020)
Nina Miolane, Susan P. Holmes
Learning Weighted Submanifolds With Variational Autoencoders and Riemannian Variational Autoencoders. CVPR (2020)
Claire Donnat, Nina Miolane, Freddy Bunbury, Jack Kreindler
A {B. ML4H@NeurIPS (2020)
Nina Miolane, Frédéric Poitevin, Yee-Ting Li, Susan P. Holmes
Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks. CVPR Workshops (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 P. Holmes, Xavier Pennec
Geomstats: A Python Package for Riemannian Geometry in Machine Learning. CoRR (2020)
Nina Miolane, Susan P. Holmes
Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders. CoRR (2019)
Nina Miolane, Frédéric Poitevin, Yee-Ting Li, Susan P. Holmes
Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks. CoRR (2019)
Johan Mathe, Nina Miolane, Nicolas Sébastien, Jeremie Lequeux
PVNet: A LRCN Architecture for Spatio-Temporal Photovoltaic PowerForecasting from Numerical Weather Prediction. CoRR (2019)
Nina Miolane, Susan P. Holmes, Xavier Pennec
Topologically Constrained Template Estimation via Morse-Smale Complexes Controls Its Statistical Consistency. SIAM J. Appl. Algebra Geom. 2 (2) (2018)
Nina Miolane, Johan Mathe, Claire Donnat, Mikael Jorda, Xavier Pennec
geomstats: a Python Package for Riemannian Geometry in Machine Learning. CoRR (2018)
Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. CoRR (2018)
Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. MICCAI (1) (2018)
Nina Miolane, Susan P. Holmes, Xavier Pennec
Template Shape Estimation: Correcting an Asymptotic Bias. SIAM J. Imaging Sci. 10 (2) (2017)
Nina Miolane, Susan P. Holmes, Xavier Pennec
Template shape estimation: correcting an asymptotic bias. CoRR (2016)
Nina Miolane, Xavier Pennec
Computing Bi-Invariant Pseudo-Metrics on Lie Groups for Consistent Statistics. Entropy 17 (4) (2015)
Nina Miolane, Xavier Pennec
Biased Estimators on Quotient Spaces. GSI (2015)
Nina Miolane, Xavier Pennec
A Survey of Mathematical Structures for Extending 2D Neurogeometry to 3D Image Processing. MCV@MICCAI (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Nina Miolane