Nina Miolane

92 papers A* 8C 1Journal 57Unranked 21
YearRankTypeTitle / Venue / Authors
2026 J jnl
Learning from Landmarks, Curves, Surfaces, and Shapes in Geomstats.
ACM Trans. Math. Softw.
Luís F. Pereira, Alice Le Brigant, Adele Myers, Emmanuel Hartman, Amil Khan, Malik Tuerkoen, Trey Dold, Mengyang Gu, Pablo Suárez-Serrato, Nina Miolane
2026 J jnl
Sequential Group Composition: A Window into the Mechanics of Deep Learning.
CoRR
Giovanni Luca Marchetti, Daniel Kunin, Adele Myers, Francisco Acosta, Nina Miolane
2025 J jnl
Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks.
CoRR
Daniel Kunin, Giovanni Luca Marchetti, Feng Chen, Dhruva Karkada, James B. Simon, Michael Robert DeWeese, Surya Ganguli, Nina Miolane
2025 J jnl
An Efficient Algorithm for the Riemannian Logarithm on the Stiefel Manifold for a Family of Riemannian Metrics.
SIAM J. Matrix Anal. Appl.
Simon Mataigne, Ralf Zimmermann, Nina Miolane
2025 J jnl
Beyond Euclid: an illustrated guide to modern machine learning with geometric, topological, and algebraic structures.
Mach. Learn. Sci. Technol.
Mathilde Papillon, Sophia Sanborn, Johan Mathe, Louisa Cornelis, Abby Bertics, Domas Buracas, Hansen Lillemark, Christian Shewmake, Fatih Dinc, Xavier Pennec, Nina Miolane
2025 A* conf
Dynamical phases of short-term memory mechanisms in RNNs.
ICML
Bariscan Kurtkaya, Fatih Dinc, Mert Yüksekgönül, Marta Blanco-Pozo, Ege Çirakman, Mark J. Schnitzer, Yucel Yemez, Hidenori Tanaka, Peng Yuan, Nina Miolane
2025 J jnl
From superposition to sparse codes: interpretable representations in neural networks.
CoRR
David A. Klindt, Charles O'Neill, Patrik Reizinger, Harald Maurer, Nina Miolane
2025 J jnl
GraphUniverse: Enabling Systematic Evaluation of Inductive Generalization.
CoRR
Louis Van Langendonck, Guillermo Bernárdez, Nina Miolane, Pere Barlet-Ros
2025 J jnl
HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations.
CoRR
Martin Carrasco, Guillermo Bernárdez, Marco Montagna, Nina Miolane, Lev Telyatnikov
2025 — conf
Learning Riemannian Metrics for Interpolating Animations.
GSI (1)
Sarah Kushner, Vismay Modi, Nina Miolane
2025 — conf
On the Approximation of the Riemannian Barycenter.
GSI (2)
Simon Mataigne, Pierre-Antoine Absil, Nina Miolane
2025 J jnl
Ordered Topological Deep Learning: a Network Modeling Case Study.
CoRR
Guillermo Bernárdez, Miquel Ferriol-Galmés, Carlos Güemes-Palau, Mathilde Papillon, Pere Barlet-Ros, Albert Cabellos-Aparicio, Nina Miolane
2025 J jnl
The Selective Disk Bispectrum and Its Inversion, with Application to Multi-Reference Alignment.
CoRR
Adele Myers, Nina Miolane
2025 J jnl
TopoBench: A Framework for Benchmarking Topological Deep Learning.
J. Data-centric Mach. Learn. Res.
Lev Telyatnikov, Guillermo Bernárdez, Marco Montagna, Mustafa Hajij, Martin Carrasco, Pavlo Vasylenko, Mathilde Papillon, Ghada Zamzmi, Michael T. Schaub, Jonas Verhellen, Pavel Snopov, Bertran Miquel-Oliver, Manel Gil-Sorribes, Alexis Molina, Victor Guallar, Theodore Long, Julian Suk, Patryk Rygiel, Alexander V. Nikitin, Giordan Escalona, Michael Banf, Dominik Filipiak, Liliya Imasheva, Max Schattauer, Alvaro L. Martinez, Halley Fritze, Marissa Masden, Valentina Sánchez, Manuel Lecha, Andrea Cavallo, Claudio Battiloro, Matthew Piekenbrock, Mauricio Tec, George Dasoulas, Nina Miolane, Simone Scardapane, Theodore Papamarkou
2025 A* conf
TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks.
ICML
Mathilde Papillon, Guillermo Bernárdez, Claudio Battiloro, Nina Miolane
2025 J jnl
Unsupervised cell segmentation by fast Gaussian Processes.
CoRR
Laura Baracaldo, Blythe King, Haoran Yan, Yizi Lin, Nina Miolane, Mengyang Gu
2025 J jnl
When Machine Learning Gets Personal: Understanding Fairness of Personalized Models.
CoRR
Louisa Cornelis, Guillermo Bernárdez, Haewon Jeong, Nina Miolane
2024 J jnl
An efficient algorithm for the Riemannian logarithm on the Stiefel manifold for a family of Riemannian metrics.
CoRR
Simon Mataigne, Ralf Zimmermann, Nina Miolane
2024 J jnl
Attending to Topological Spaces: The Cellular Transformer.
CoRR
Rubén Ballester, Pablo Hernández-García, Mathilde Papillon, Claudio Battiloro, Nina Miolane, Tolga Birdal, Carles Casacuberta, Sergio Escalera, Mustafa Hajij
2024 J jnl
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures.
CoRR
Sophia Sanborn, Johan Mathe, Mathilde Papillon, Domas Buracas, Hansen Lillemark, Christian Shewmake, Abby Bertics, Xavier Pennec, Nina Miolane
2024 J jnl
Bounds on the geodesic distances on the Stiefel manifold for a family of Riemannian metrics.
CoRR
Simon Mataigne, Pierre-Antoine Absil, Nina Miolane
2024 A* conf
Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems.
NeurIPS
Francisco Acosta, Fatih Dinc, William Redman, Manu S. Madhav, David A. Klindt, Nina Miolane
2024 — conf
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.
GRaM
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane
2024 J jnl
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.
CoRR
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree P. Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane
2024 J jnl
Learning from landmarks, curves, surfaces, and shapes in Geomstats.
CoRR
Luís F. Pereira, Alice Le Brigant, Adele Myers, Emmanuel Hartman, Amil Khan, Malik Tuerkoen, Trey Dold, Mengyang Gu, Pablo Suárez-Serrato, Nina Miolane
2024 A* conf
Not so griddy: Internal representations of RNNs path integrating more than one agent.
NeurIPS
William Redman, Francisco Acosta, Santiago Acosta-Mendoza, Nina Miolane
2024 — conf
On Accuracy and Speed of Geodesic Regression: Do Geometric Priors Improve Learning on Small Datasets?
CVPR Workshops
Adele Myers, Nina Miolane
2024 J jnl
Position Paper: Challenges and Opportunities in Topological Deep Learning.
CoRR
Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. 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
2024 A* conf
Position: Topological Deep Learning is the New Frontier for Relational Learning.
ICML
Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, 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
2024 A* conf
The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks.
NeurIPS
Simon Mataigne, Johan Mathe, Sophia Sanborn, Christopher Hillar, Nina Miolane
2024 J jnl
The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks.
CoRR
Simon Mataigne, Johan Mathe, Sophia Sanborn, Christopher Hillar, Nina Miolane
2024 J jnl
TopoBenchmarkX: A Framework for Benchmarking Topological Deep Learning.
CoRR
Lev Telyatnikov, Guillermo Bernárdez, Marco Montagna, Pavlo Vasylenko, Ghada Zamzmi, Mustafa Hajij, Michael T. Schaub, Nina Miolane, Simone Scardapane, Theodore Papamarkou
2024 J jnl
TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks.
CoRR
Mathilde Papillon, Guillermo Bernárdez, Claudio Battiloro, Nina Miolane
2024 J jnl
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains.
CoRR
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
2024 J jnl
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains.
J. Mach. Learn. Res.
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
2023 A* conf
A General Framework for Robust G-Invariance in G-Equivariant Networks.
NeurIPS
Sophia Sanborn, Nina Miolane
2023 J jnl
A General Framework for Robust G-Invariance in G-Equivariant Networks.
CoRR
Sophia Sanborn, Nina Miolane
2023 J jnl
Architectures of Topological Deep Learning: A Survey on Topological Neural Networks.
CoRR
Mathilde Papillon, Sophia Sanborn, Mustafa Hajij, Nina Miolane
2023 J jnl
Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metric.
Trans. Mach. Learn. Res.
Saiteja Utpala, Praneeth Vepakomma, Nina Miolane
2023 — conf
Geodesic Regression Characterizes 3D Shape Changes in the Female Brain During Menstruation.
ICCV (Workshops)
Adele Myers, Caitlin M. Taylor, Emily G. Jacobs, Nina Miolane
2023 J jnl
Geodesic Regression Characterizes 3D Shape Changes in the Female Brain During Menstruation.
CoRR
Adele Myers, Caitlin M. Taylor, Emily G. Jacobs, Nina Miolane
2023 — conf
Group Equivariant Sparse Coding.
GSI (1)
Christian Shewmake, Nina Miolane, Bruno A. Olshausen
2023 — conf
ICML 2023 Topological Deep Learning Challenge: Design and Results.
TAG-ML
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
2023 J jnl
Identifying Interpretable Visual Features in Artificial and Biological Neural Systems.
CoRR
David A. Klindt, Sophia Sanborn, Francisco Acosta, Frédéric Poitevin, Nina Miolane
2023 J jnl
Introduction to Riemannian Geometry and Geometric Statistics: From Basic Theory to Implementation with Geomstats.
Found. Trends Mach. Learn.
Nicolas Guigui, Nina Miolane, Xavier Pennec
2023 — ed.
NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 16 December 2023, New Orleans, Lousiana, USA.
NeurReps
Sophia Sanborn, Christian Shewmake, Simone Azeglio, Nina Miolane
2023 J jnl
Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets.
Frontiers Bioinform.
Wanxin Li, Jules Mirone, Ashok Prasad, Nina Miolane, Carine Legrand, Khanh Dao Duc
2023 J jnl
Parametric Information Geometry with the Package Geomstats.
ACM Trans. Math. Softw.
Alice Le Brigant, Jules Deschamps, Antoine Collas, Nina Miolane
2023 — conf
Preface.
NeurReps
Sophia Sanborn, Christian Shewmake, Simone Azeglio, Nina Miolane
2023 — conf
Preface.
TAG-ML
Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
2023 — conf
Quantifying Extrinsic Curvature in Neural Manifolds.
CVPR Workshops
Francisco Acosta, Sophia Sanborn, Khanh Dao Duc, Manu S. Madhav, Nina Miolane
2023 J jnl
Reconstructing Heterogeneous Cryo-EM Molecular Structures by Decomposing Them into Polymer Chains.
CoRR
Bongjin Koo, Julien N. P. Martel, Ariana Peck, Axel Levy, Frédéric Poitevin, Nina Miolane
2023 — ed.
Topological, Algebraic and Geometric Learning Workshops 2023, 28 July 2023, Honolulu, HI, USA
TAG-ML
Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
2022 — conf
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images.
ECCV (21)
Axel Levy, Frédéric Poitevin, Julien N. P. Martel, Youssef S. G. Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, Gordon Wetzstein
2022 J jnl
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images.
CoRR
Axel Levy, Frédéric Poitevin, Julien N. P. Martel, Youssef S. G. Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, Gordon Wetzstein
2022 J jnl
Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopy.
CoRR
Claire Donnat, Axel Levy, Frédéric Poitevin, Nina Miolane
2022 J jnl
Defining an action of SO(d)-rotations on images generated by projections of d-dimensional objects: Applications to pose inference with Geometric VAEs.
CoRR
Nicolas Legendre, Khanh Dao Duc, Nina Miolane
2022 J jnl
Heterogeneous reconstruction of deformable atomic models in Cryo-EM.
CoRR
Youssef S. G. Nashed, Ariana Peck, Julien N. P. Martel, Axel Levy, Bongjin Koo, Gordon Wetzstein, Nina Miolane, Daniel Ratner, Frédéric Poitevin
2022 J jnl
Higher-Order Attention Networks.
CoRR
Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou, Nina Miolane, Aldo Guzmán-Sáenz, Karthikeyan Natesan Ramamurthy
2022 — conf
ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results.
TAG-ML
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
2022 J jnl
ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results.
CoRR
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 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
2022 J jnl
Intentional Choreography with Semi-Supervised Recurrent VAEs.
CoRR
Mathilde Papillon, Mariel Pettee, Nina Miolane
2022 — ed.
NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 03 December 2022, New Orleans, Lousiana, USA
NeurReps
Sophia Sanborn, Christian Shewmake, Simone Azeglio, Arianna Di Bernardo, Nina Miolane
2022 J jnl
Parametric information geometry with the package Geomstats.
CoRR
Alice Le Brigant, Jules Deschamps, Antoine Collas, Nina Miolane
2022 C conf
PirouNet: Creating Dance Through Artist-Centric Deep Learning.
ArtsIT
Mathilde Papillon, Mariel Pettee, Nina Miolane
2022 J jnl
PirouNet: Creating Intentional Dance with Semi-Supervised Conditional Recurrent Variational Autoencoders.
CoRR
Mathilde Papillon, Mariel Pettee, Nina Miolane
2022 — conf
Preface.
NeurReps
Sophia Sanborn, Christian Shewmake, Simone Azeglio, Arianna Di Bernardo, Nina Miolane
2022 — conf
Preface.
TAG-ML
Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf
2022 J jnl
Regression-Based Elastic Metric Learning on Shape Spaces of Elastic Curves.
CoRR
Adele Myers, Nina Miolane
2022 J jnl
Testing geometric representation hypotheses from simulated place cell recordings.
CoRR
Thibault Niederhauser, Adam Lester, Nina Miolane, Khanh Dao Duc, Manu S. Madhav
2022 — ed.
Topological, Algebraic and Geometric Learning Workshops 2022, 25-22 July 2022, Virtual
TAG-ML
Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf
2021 J jnl
ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results.
CoRR
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
2021 J jnl
Riemannian Functional Map Synchronization for Probabilistic Partial Correspondence in Shape Networks.
CoRR
Faria Huq, Adrish Dey, Sahra Yusuf, Dena Bazazian, Tolga Birdal, Nina Miolane
2021 — conf
Using a Riemannian Elastic Metric for Statistical Analysis of Tumor Cell Shape Heterogeneity.
GSI (2)
Wanxin Li, Ashok Prasad, Nina Miolane, Khanh Dao Duc
2020 — conf
A {B.
ML4H@NeurIPS
Claire Donnat, Nina Miolane, Freddy Bunbury, Jack Kreindler
2020 — conf
Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks.
CVPR Workshops
Nina Miolane, Frédéric Poitevin, Yee-Ting Li, Susan P. Holmes
2020 J jnl
Geomstats: A Python Package for Riemannian Geometry in Machine Learning.
CoRR
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
2020 — conf
Introduction to Geometric Learning in Python with Geomstats.
SciPy
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
2020 A* conf
Learning Weighted Submanifolds With Variational Autoencoders and Riemannian Variational Autoencoders.
CVPR
Nina Miolane, Susan P. Holmes
2019 J jnl
Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks.
CoRR
Nina Miolane, Frédéric Poitevin, Yee-Ting Li, Susan P. Holmes
2019 J jnl
Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders.
CoRR
Nina Miolane, Susan P. Holmes
2019 J jnl
PVNet: A LRCN Architecture for Spatio-Temporal Photovoltaic PowerForecasting from Numerical Weather Prediction.
CoRR
Johan Mathe, Nina Miolane, Nicolas Sébastien, Jeremie Lequeux
2018 — conf
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry.
MICCAI (1)
Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz
2018 J jnl
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry.
CoRR
Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz
2018 J jnl
Topologically Constrained Template Estimation via Morse-Smale Complexes Controls Its Statistical Consistency.
SIAM J. Appl. Algebra Geom.
Nina Miolane, Susan P. Holmes, Xavier Pennec
2018 J jnl
geomstats: a Python Package for Riemannian Geometry in Machine Learning.
CoRR
Nina Miolane, Johan Mathe, Claire Donnat, Mikael Jorda, Xavier Pennec
2017 J jnl
Template Shape Estimation: Correcting an Asymptotic Bias.
SIAM J. Imaging Sci.
Nina Miolane, Susan P. Holmes, Xavier Pennec
2016 — —
Geometric Statistics for Computational Anatomy. (Les statistiques géométriques pour l'anatomie numérique).
Nina Miolane
2016 J jnl
Template shape estimation: correcting an asymptotic bias.
CoRR
Nina Miolane, Susan P. Holmes, Xavier Pennec
2015 — conf
A Survey of Mathematical Structures for Extending 2D Neurogeometry to 3D Image Processing.
MCV@MICCAI
Nina Miolane, Xavier Pennec
2015 — conf
Biased Estimators on Quotient Spaces.
GSI
Nina Miolane, Xavier Pennec
2015 J jnl
Computing Bi-Invariant Pseudo-Metrics on Lie Groups for Consistent Statistics.
Entropy
Nina Miolane, Xavier Pennec