Multilayer Scattering Image Analysis Fits fMRI Activity in Visual Areas. - Michael Eickenberg; Alexandre Gramfort; Bertrand Thirion (PRNI, 2012)

Characterizing Responses of Translation-Invariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions. - Michael Eickenberg; Ryan J. Rowekamp; Minjoon Kouh; Tatyana O. Sharpee (Neural Comput., 2012)

Second Order Scattering Descriptors Predict fMRI Activity Due to Visual Textures. - Michael Eickenberg; Mehdi Senoussi; Fabian Pedregosa; Alexandre Gramfort; Bertrand Thirion (PRNI, 2013)

HRF Estimation Improves Sensitivity of fMRI Encoding and Decoding Models. - Fabian Pedregosa; Michael Eickenberg; Bertrand Thirion; Alexandre Gramfort (PRNI, 2013)

Machine learning for neuroimaging with scikit-learn. - Alexandre Abraham; Fabian Pedregosa; Michael Eickenberg; Philippe Gervais; Andreas Mueller; Jean Kossaifi; Alexandre Gramfort; Bertrand Thirion; Gaël Varoquaux (Frontiers Neuroinformatics, 2014)

Grouping Total Variation and Sparsity: Statistical Learning with Segmenting Penalties. - Michael Eickenberg; Elvis Dohmatob; Bertrand Thirion; Gaël Varoquaux (MICCAI (1), 2015)

Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease. - Mehdi Rahim; Bertrand Thirion; Alexandre Abraham; Michael Eickenberg; Elvis Dohmatob; Claude Comtat; Gaël Varoquaux (MICCAI (1), 2015)

Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data. - Danilo Bzdok; Michael Eickenberg; Olivier Grisel; Bertrand Thirion; Gaël Varoquaux (NIPS, 2015)

Speeding-Up Model-Selection in Graphnet via Early-Stopping and Univariate Feature-Screening. - Elvis Dohmatob; Michael Eickenberg; Bertrand Thirion; Gaël Varoquaux (PRNI, 2015)

FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging. - Gaël Varoquaux; Michael Eickenberg; Elvis Dohmatob; Bertrand Thirion (CoRR, 2015)

Data-driven HRF estimation for encoding and decoding models. - Fabian Pedregosa; Michael Eickenberg; Philippe Ciuciu; Bertrand Thirion; Alexandre Gramfort (NeuroImage, 2015)

Evaluating Computational Models of Vision with Functional Magnetic Resonance Imaging. (Évaluation de modèles computationnels de la vision humaine en imagerie par résonance magnétique fonctionnelle). - Michael Eickenberg (2015)

Local Q-linear convergence and finite-time active set identification of ADMM on a class of penalized regression problems. - Elvis Dohmatob; Michael Eickenberg; Bertrand Thirion; Gaël Varoquaux (ICASSP, 2016)

Formal Models of the Network Co-occurrence Underlying Mental Operations. - Danilo Bzdok; Gaël Varoquaux; Olivier Grisel; Michael Eickenberg; Cyril Poupon; Bertrand Thirion (PLoS Comput. Biol., 2016)

Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging. - Danilo Bzdok; Michael Eickenberg; Gaël Varoquaux; Bertrand Thirion (IPMI, 2017)

Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities. - Michael Eickenberg; Georgios Exarchakis; Matthew J. Hirn; Stéphane Mallat (NIPS, 2017)

Convolutional Network Layers Map the Function of the Human Visual Cortex. - Michael Eickenberg; Gaël Varoquaux; Bertrand Thirion; Alexandre Gramfort (ERCIM News, 2017)

Seeing it all: Convolutional network layers map the function of the human visual system. - Michael Eickenberg; Alexandre Gramfort; Gaël Varoquaux; Bertrand Thirion (NeuroImage, 2017)

Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties. - Michael Eickenberg; Georgios Exarchakis; Matthew J. Hirn; Stéphane Mallat; Louis Thiry (CoRR, 2018)

Kymatio: Scattering Transforms in Python. - Mathieu Andreux; Tomás Angles; Georgios Exarchakis; Roberto Leonarduzzi; Gaspar Rochette; Louis Thiry; John Zarka; Stéphane Mallat; Joakim Andén; Eugene Belilovsky; Joan Bruna; Vincent Lostanlen; et al. (CoRR, 2018)

Greedy Layerwise Learning Can Scale To ImageNet. - Eugene Belilovsky; Michael Eickenberg; Edouard Oyallon (ICML, 2019)

Arrhythmia Classification of 12-lead Electrocardiograms by Hybrid Scattering-LSTM Networks. - Philip A. Warrick; Vincent Lostanlen; Michael Eickenberg; Joakim Andén; Masun Nabhan Homsi (CinC, 2020)

Decoupled Greedy Learning of CNNs. - Eugene Belilovsky; Michael Eickenberg; Edouard Oyallon (ICML, 2020)

Kymatio: Scattering Transforms in Python. - Mathieu Andreux; Tomás Angles; Georgios Exarchakis; Roberto Leonarduzzi; Gaspar Rochette; Louis Thiry; John Zarka; Stéphane Mallat; Joakim Andén; Eugene Belilovsky; Joan Bruna; Vincent Lostanlen; et al. (J. Mach. Learn. Res., 2020)

Arrhythmia Classification of Reduced-Lead Electrocardiograms by Scattering-Recurrent Networks. - Philip A. Warrick; Vincent Lostanlen; Michael Eickenberg; Masun Nabhan Homsi; Adrián Campoy Rodríguez; Joakim Andén (CinC, 2021)

Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. - Hannah Lawrence; David Barmherzig; Henry Li; Michael Eickenberg; Marylou Gabrié (MSML, 2021)

Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning. - Eugene Belilovsky; Louis Leconte; Lucas Caccia; Michael Eickenberg; Edouard Oyallon (CoRR, 2021)

Parametric Scattering Networks. - Shanel Gauthier; Benjamin Thérien; Laurent Alsène-Racicot; Irina Rish; Eugene Belilovsky; Michael Eickenberg; Guy Wolf (CoRR, 2021)

The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence. - Francisco Villaescusa-Navarro; Shy Genel; Daniel Angles-Alcazar; Leander Thiele; Romeel Dave; Desika Narayanan; Andrina Nicola; Yin Li 009; Pablo Villanueva-Domingo; Benjamin D. Wandelt; David N. Spergel; Rachel S. Somerville; et al. (CoRR, 2021)

Parametric Scattering Networks. - Shanel Gauthier; Benjamin Thérien; Laurent Alsène-Racicot; Muawiz Chaudhary; Irina Rish; Eugene Belilovsky; Michael Eickenberg; Guy Wolf (CVPR, 2022)

The CAMELS project: public data release. - Francisco Villaescusa-Navarro; Shy Genel; Daniel Anglés-Alcázar; Lucia A. Perez; Pablo Villanueva-Domingo; Digvijay Wadekar; Helen Shao; Faizan G. Mohammad; Sultan Hassan; Emily Moser; Erwin T. Lau; Luis Fernando Machado Poletti Valle; et al. (CoRR, 2022)

Feature-space selection with banded ridge regression. - Tom Dupré la Tour; Michael Eickenberg; Anwar Nunez-Elizalde; Jack L. Gallant (NeuroImage, 2022)

Can Forward Gradient Match Backpropagation? - Louis Fournier; Stéphane Rivaud; Eugene Belilovsky; Michael Eickenberg; Edouard Oyallon (ICML, 2023)

Local Learning with Neuron Groups. - Adeetya Patel; Michael Eickenberg; Eugene Belilovsky (CoRR, 2023)

Learnable wavelet neural networks for cosmological inference. - Christian Pedersen; Michael Eickenberg; Shirley Ho (CoRR, 2023)

xVal: A Continuous Number Encoding for Large Language Models. - Siavash Golkar; Mariel Pettee; Michael Eickenberg; Alberto Bietti; Miles D. Cranmer; Géraud Krawezik; François Lanusse; Michael McCabe; Ruben Ohana; Liam Holden Parker; Bruno Régaldo-Saint Blancard; Tiberiu Tesileanu; et al. (CoRR, 2023)

Multiple Physics Pretraining for Physical Surrogate Models. - Michael McCabe; Bruno Régaldo-Saint Blancard; Liam Holden Parker; Ruben Ohana; Miles D. Cranmer; Alberto Bietti; Michael Eickenberg; Siavash Golkar; Géraud Krawezik; François Lanusse; Mariel Pettee; Tiberiu Tesileanu; et al. (CoRR, 2023)

AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models. - François Lanusse; Liam Holden Parker; Siavash Golkar; Miles D. Cranmer; Alberto Bietti; Michael Eickenberg; Géraud Krawezik; Michael McCabe; Ruben Ohana; Mariel Pettee; Bruno Régaldo-Saint Blancard; Tiberiu Tesileanu; et al. (CoRR, 2023)

SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering. - Pablo Lemos; Liam Holden Parker; ChangHoon Hahn; Shirley Ho; Michael Eickenberg; Jiamin Hou; Elena Massara; Chirag Modi 002; Azadeh Moradinezhad Dizgah; Bruno Régaldo-Saint Blancard; David N. Spergel (CoRR, 2023)

Robust simulation-based inference in cosmology with Bayesian neural networks. - Pablo Lemos; Miles D. Cranmer; Muntazir Abidi; ChangHoon Hahn; Michael Eickenberg; Elena Massara; David Yallup; Shirley Ho (Mach. Learn. Sci. Technol., 2023)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexis Thual; Alisha Kodibagkar; Amadeus Kanaan; et al. (Zenodo, 2023)

Adversarial Attacks on the Interpretation of Neuron Activation Maximization. - Géraldin Nanfack; Alexander Fulleringer; Jonathan Marty; Michael Eickenberg; Eugene Belilovsky (AAAI, 2024)

Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation. - Pedro Vianna; Muawiz Sajjad Chaudhary; Paria Mehrbod; An Tang; Guy Cloutier; Guy Wolf; Michael Eickenberg; Eugene Belilovsky (CoLLAs, 2024)

MoMo: Momentum Models for Adaptive Learning Rates. - Fabian Schaipp; Ruben Ohana; Michael Eickenberg; Aaron Defazio; Robert M. Gower (ICML, 2024)

Multiple Physics Pretraining for Spatiotemporal Surrogate Models. - Michael McCabe; Bruno Régaldo-Saint Blancard; Liam Holden Parker; Ruben Ohana; Miles D. Cranmer; Alberto Bietti; Michael Eickenberg; Siavash Golkar; Géraud Krawezik; François Lanusse; Mariel Pettee; Tiberiu Tesileanu; et al. (NeurIPS, 2024)

From Feature Visualization to Visual Circuits: Effect of Adversarial Model Manipulation. - Géraldin Nanfack; Michael Eickenberg; Eugene Belilovsky (CoRR, 2024)

Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task. - Siavash Golkar; Alberto Bietti; Mariel Pettee; Michael Eickenberg; Miles D. Cranmer; Keiya Hirashima; Géraud Krawezik; Nicholas Lourie; Michael McCabe; Rudy Morel; Ruben Ohana; Liam Holden Parker; et al. (CoRR, 2024)

Statistical Component Separation for Targeted Signal Recovery in Noisy Mixtures. - Bruno Régaldo-Saint Blancard; Michael Eickenberg (Trans. Mach. Learn. Res., 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexis Thual; Alisha Kodibagkar; Amadeus Kanaan; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexis Thual; Alisha Kodibagkar; Amadeus Kanaan; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2024)

PETRA: Parallel End-to-end Training with Reversible Architectures. - Stéphane Rivaud; Louis Fournier; Thomas Pumir; Eugene Belilovsky; Michael Eickenberg; Edouard Oyallon (ICLR, 2025)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2025)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2025)

Surfer-H Meets Holo1: Cost-Efficient Web Agent Powered by Open Weights. - Mathieu Andreux; Breno Baldas Skuk; Hamza Benchekroun; Emilien Biré; Antoine Bonnet; Riaz Bordie; Nathan Bout; Matthias Brunel; Pierre-Louis Cedoz; Antoine Chassang; Mickaël Chen; Alexandra D. Constantinou; et al. (CoRR, 2025)