Miolane, Nina

22 publications

NeurIPS 2025 Alternating Gradient Flows: A Theory of Feature Learning in Two-Layer Neural Networks Daniel Kunin, Giovanni Luca Marchetti, Feng Chen, Dhruva Karkada, James B Simon, Michael R DeWeese, Surya Ganguli, Nina Miolane

ICML 2025 Dynamical Phases of Short-Term Memory Mechanisms in RNNs Bariscan Kurtkaya, Fatih Dinc, Mert Yuksekgonul, Marta Blanco-Pozo, Ege Cirakman, Mark Schnitzer, Yucel Yemez, Hidenori Tanaka, Peng Yuan, Nina Miolane

ICML 2025 TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks Mathilde Papillon, Guillermo Bernardez, Claudio Battiloro, Nina Miolane

NeurIPS 2024 Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems Francisco Acosta, Fatih Dinc, William T. Redman, Manu Madhav, David Klindt, Nina Miolane

NeurIPS 2024 Not so Griddy: Internal Representations of RNNs Path Integrating More than One Agent William T. Redman, Francisco Acosta, Santiago Acosta-Mendoza, Nina Miolane

NeurIPSW 2024 Not so Griddy: Internal Representations of RNNs Path Integrating More than One Agent William T Redman, Francisco Acosta, Santiago Acosta-Mendoza, Nina Miolane

CVPRW 2024 On Accuracy and Speed of Geodesic Regression: Do Geometric Priors Improve Learning on Small Datasets? Adele Myers, Nina Miolane

ICML 2024 Position: Topological Deep Learning Is the New Frontier for Relational Learning 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 Veličković, Bei Wang, Yusu Wang, Guowei Wei, Ghada Zamzmi

NeurIPS 2024 The Selective $g$-Bispectrum and Its Inversion: Applications to $g$-Invariant Networks Simon Mataigne, Johan Mathe, Sophia Sanborn, Christopher Hillar, Nina Miolane

MLOSS 2024 TopoX: A Suite of Python Packages for Machine Learning on Topological Domains 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

NeurIPS 2023 A General Framework for Robust G-Invariance in G-Equivariant Networks Sophia Sanborn, Nina Miolane

TMLR 2023 Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with Log-Euclidean Metric Saiteja Utpala, Praneeth Vepakomma, Nina Miolane

NeurIPSW 2023 Evaluation of Representational Similarity Scores Across Human Visual Cortex Francisco Acosta, Colin Conwell, Sophia Sanborn, David A. Klindt, Nina Miolane

ICCVW 2023 Geodesic Regression Characterizes 3D Shape Changes in the Female Brain During Menstruation Adele Myers, Caitlin M. Taylor, Emily G. Jacobs, Nina Miolane

FnTML 2023 Introduction to Riemannian Geometry and Geometric Statistics: From Basic Theory to Implementation with Geomstats Nicolas Guigui, Nina Miolane, Xavier Pennec

CVPRW 2023 Quantifying Extrinsic Curvature in Neural Manifolds Francisco Acosta, Sophia Sanborn, Khanh Dao Duc, Manu S. Madhav, Nina Miolane

NeurIPSW 2023 Visual Scene Representation with Hierarchical Equivariant Sparse Coding Christian A Shewmake, Domas Buracas, Hansen Lillemark, Jinho Shin, Erik J Bekkers, Nina Miolane, Bruno Olshausen

ECCV 2022 CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images Axel Levy, Frédéric Poitevin, Julien Martel, Youssef Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, Gordon Wetzstein

NeurIPSW 2022 Regression-Based Elastic Metric Learning on Shape Spaces of Cell Curves Adele Myers, Nina Miolane

NeurIPSW 2022 Testing Geometric Representation Hypotheses from Simulated Place Cell Recordings Thibault Niederhauser, Adam Lester, Nina Miolane, Khanh Dao Duc, Manu Madhav

CVPRW 2020 Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks Nina Miolane, Frédéric Poitevin, Yee-Ting Li, Susan P. Holmes

MLOSS 2020 Geomstats: A Python Package for Riemannian Geometry in Machine Learning Nina Miolane, Nicolas Guigui, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Daniel Brooks, Bernhard Kainz, Claire Donnat, Susan Holmes, Xavier Pennec