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2020 – today
- 2024
[j9]Bruno Régaldo-Saint Blancard, Michael Eickenberg:
Statistical Component Separation for Targeted Signal Recovery in Noisy Mixtures. Trans. Mach. Learn. Res. 2024 (2024)- [c19]Géraldin Nanfack, Alexander Fulleringer, Jonathan Marty, Michael Eickenberg, Eugene Belilovsky:
Adversarial Attacks on the Interpretation of Neuron Activation Maximization. AAAI 2024: 4315-4324 - [c18]Fabian Schaipp, Ruben Ohana, Michael Eickenberg, Aaron Defazio, Robert M. Gower:
MoMo: Momentum Models for Adaptive Learning Rates. ICML 2024 - [i30]Pedro Vianna, Muawiz Chaudhary, Paria Mehrbod, An Tang, Guy Cloutier, Guy Wolf, Michael Eickenberg, Eugene Belilovsky:
Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation. CoRR abs/2402.04958 (2024) - [i29]Géraldin Nanfack, Michael Eickenberg, Eugene Belilovsky:
From Feature Visualization to Visual Circuits: Effect of Adversarial Model Manipulation. CoRR abs/2406.01365 (2024) - [i28]Stéphane Rivaud, Louis Fournier, Thomas Pumir, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon:
PETRA: Parallel End-to-end Training with Reversible Architectures. CoRR abs/2406.02052 (2024) - [i27]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, Bruno Régaldo-Saint Blancard, Kyunghyun Cho, Shirley Ho:
Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task. CoRR abs/2406.02585 (2024) - 2023
- [j8]Pablo Lemos, Miles D. Cranmer, Muntazir Abidi, ChangHoon Hahn, Michael Eickenberg, Elena Massara, David Yallup, Shirley Ho:
Robust simulation-based inference in cosmology with Bayesian neural networks. Mach. Learn. Sci. Technol. 4(1): 01 (2023) - [c17]Louis Fournier, Stéphane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon:
Can Forward Gradient Match Backpropagation? ICML 2023: 10249-10264 - [i26]Adeetya Patel, Michael Eickenberg, Eugene Belilovsky:
Local Learning with Neuron Groups. CoRR abs/2301.07635 (2023) - [i25]Fabian Schaipp, Ruben Ohana, Michael Eickenberg, Aaron Defazio, Robert M. Gower:
MoMo: Momentum Models for Adaptive Learning Rates. CoRR abs/2305.07583 (2023) - [i24]Louis Fournier, Stéphane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon:
Can Forward Gradient Match Backpropagation? CoRR abs/2306.06968 (2023) - [i23]Géraldin Nanfack, Alexander Fulleringer, Jonathan Marty, Michael Eickenberg, Eugene Belilovsky:
Adversarial Attacks on the Interpretation of Neuron Activation Maximization. CoRR abs/2306.07397 (2023) - [i22]Bruno Régaldo-Saint Blancard, Michael Eickenberg:
Statistical Component Separation for Targeted Signal Recovery in Noisy Mixtures. CoRR abs/2306.15012 (2023) - [i21]Christian Pedersen, Michael Eickenberg, Shirley Ho:
Learnable wavelet neural networks for cosmological inference. CoRR abs/2307.14362 (2023) - [i20]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, Kyunghyun Cho, Shirley Ho:
xVal: A Continuous Number Encoding for Large Language Models. CoRR abs/2310.02989 (2023) - [i19]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, Kyunghyun Cho, Shirley Ho:
Multiple Physics Pretraining for Physical Surrogate Models. CoRR abs/2310.02994 (2023) - [i18]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, Kyunghyun Cho, Shirley Ho:
AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models. CoRR abs/2310.03024 (2023) - [i17]Pablo Lemos, Liam Holden Parker, ChangHoon Hahn, Shirley Ho, Michael Eickenberg, Jiamin Hou, Elena Massara, Chirag Modi, Azadeh Moradinezhad Dizgah, Bruno Régaldo-Saint Blancard, David N. Spergel:
SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering. CoRR abs/2310.15256 (2023) - 2022
- [j7]Tom Dupré la Tour, Michael Eickenberg, Anwar Nunez-Elizalde, Jack L. Gallant:
Feature-space selection with banded ridge regression. NeuroImage 264: 119728 (2022) - [c16]Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf:
Parametric Scattering Networks. CVPR 2022: 5739-5748 - [i16]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, Andrina Nicola, Leander Thiele, Yongseok Jo, Oliver H. E. Philcox, Benjamin D. Oppenheimer, Megan Tillman, ChangHoon Hahn, Neerav Kaushal, Alice Pisani, Matthew Gebhardt, Ana Maria Delgado, Joyce Caliendo, Christina Kreisch, Kaze W. K. Wong, William R. Coulton, Michael Eickenberg, Gabriele Parimbelli, Yueying Ni, Ulrich P. Steinwandel, Valentina La Torre, Romeel Dave, Nicholas Battaglia, Daisuke Nagai, David N. Spergel, Lars Hernquist, Blakesley Burkhart, Desika Narayanan, Benjamin D. Wandelt, Rachel S. Somerville, Greg L. Bryan, Matteo Viel, Yin Li, Vid Irsic, Katarina Kraljic, Mark Vogelsberger:
The CAMELS project: public data release. CoRR abs/2201.01300 (2022) - [i15]Pablo Lemos, Miles D. Cranmer, Muntazir Abidi, ChangHoon Hahn, Michael Eickenberg, Elena Massara, David Yallup, Shirley Ho:
Robust Simulation-Based Inference in Cosmology with Bayesian Neural Networks. CoRR abs/2207.08435 (2022) - 2021
- [c15]Philip A. Warrick, Vincent Lostanlen, Michael Eickenberg, Masun Nabhan Homsi, Adrián Campoy Rodríguez, Joakim Andén:
Arrhythmia Classification of Reduced-Lead Electrocardiograms by Scattering-Recurrent Networks. CinC 2021: 1-4 - [c14]Hannah Lawrence, David Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrié:
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. MSML 2021: 516-567 - [i14]Eugene Belilovsky, Louis Leconte, Lucas Caccia, Michael Eickenberg, Edouard Oyallon:
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning. CoRR abs/2106.06401 (2021) - [i13]Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf:
Parametric Scattering Networks. CoRR abs/2107.09539 (2021) - [i12]Francisco Villaescusa-Navarro, Shy Genel, Daniel Angles-Alcazar, Leander Thiele, Romeel Dave, Desika Narayanan, Andrina Nicola, Yin Li, Pablo Villanueva-Domingo, Benjamin D. Wandelt, David N. Spergel, Rachel S. Somerville, José Manuel Zorrilla Matilla, Faizan G. Mohammad, Sultan Hassan, Helen Shao, Digvijay Wadekar, Michael Eickenberg, Kaze W. K. Wong, Gabriella Contardo, Yongseok Jo, Emily Moser, Erwin T. Lau, Luis Fernando Machado Poletti Valle, Lucia A. Perez, Daisuke Nagai, Nicholas Battaglia, Mark Vogelsberger:
The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence. CoRR abs/2109.10915 (2021) - 2020
- [j6]Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg:
Kymatio: Scattering Transforms in Python. J. Mach. Learn. Res. 21: 60:1-60:6 (2020) - [c13]Philip A. Warrick, Vincent Lostanlen, Michael Eickenberg, Joakim Andén, Masun Nabhan Homsi:
Arrhythmia Classification of 12-lead Electrocardiograms by Hybrid Scattering-LSTM Networks. CinC 2020: 1-4 - [c12]Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon:
Decoupled Greedy Learning of CNNs. ICML 2020: 736-745 - [i11]Hannah Lawrence, David A. Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrié:
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. CoRR abs/2012.07386 (2020)
2010 – 2019
- 2019
- [c11]Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon:
Greedy Layerwise Learning Can Scale To ImageNet. ICML 2019: 583-593 - [i10]Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon:
Decoupled Greedy Learning of CNNs. CoRR abs/1901.08164 (2019) - 2018
- [i9]Michael Eickenberg, Georgios Exarchakis, Matthew J. Hirn, Stéphane Mallat, Louis Thiry:
Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties. CoRR abs/1805.00571 (2018) - [i8]Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg:
Kymatio: Scattering Transforms in Python. CoRR abs/1812.11214 (2018) - [i7]Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon:
Greedy Layerwise Learning Can Scale to ImageNet. CoRR abs/1812.11446 (2018) - 2017
- [j5]Michael Eickenberg, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion:
Seeing it all: Convolutional network layers map the function of the human visual system. NeuroImage 152: 184-194 (2017) - [c10]Danilo Bzdok, Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion:
Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging. IPMI 2017: 323-335 - [c9]Michael Eickenberg, Georgios Exarchakis, Matthew J. Hirn, Stéphane Mallat:
Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities. NIPS 2017: 6540-6549 - [i6]Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort:
Convolutional Network Layers Map the Function of the Human Visual Cortex. ERCIM News 2017(108) (2017) - 2016
- [j4]Danilo Bzdok, Gaël Varoquaux, Olivier Grisel, Michael Eickenberg, Cyril Poupon, Bertrand Thirion:
Formal Models of the Network Co-occurrence Underlying Mental Operations. PLoS Comput. Biol. 12(6) (2016) - [c8]Elvis Dohmatob, Michael Eickenberg, Bertrand Thirion, Gaël Varoquaux:
Local Q-linear convergence and finite-time active set identification of ADMM on a class of penalized regression problems. ICASSP 2016: 4752-4756 - 2015
- [b1]Michael Eickenberg:
Evaluating Computational Models of Vision with Functional Magnetic Resonance Imaging. (Évaluation de modèles computationnels de la vision humaine en imagerie par résonance magnétique fonctionnelle). University of Paris-Sud, Orsay, France, 2015 - [j3]Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Bertrand Thirion, Alexandre Gramfort:
Data-driven HRF estimation for encoding and decoding models. NeuroImage 104: 209-220 (2015) - [c7]Mehdi Rahim, Bertrand Thirion, Alexandre Abraham, Michael Eickenberg, Elvis Dohmatob, Claude Comtat, Gaël Varoquaux:
Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease. MICCAI (1) 2015: 207-214 - [c6]Michael Eickenberg, Elvis Dohmatob, Bertrand Thirion, Gaël Varoquaux:
Grouping Total Variation and Sparsity: Statistical Learning with Segmenting Penalties. MICCAI (1) 2015: 685-693 - [c5]Danilo Bzdok, Michael Eickenberg, Olivier Grisel, Bertrand Thirion, Gaël Varoquaux:
Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data. NIPS 2015: 3348-3356 - [c4]Elvis Dohmatob, Michael Eickenberg, Bertrand Thirion, Gaël Varoquaux:
Speeding-Up Model-Selection in Graphnet via Early-Stopping and Univariate Feature-Screening. PRNI 2015: 17-20 - [i5]Gaël Varoquaux, Michael Eickenberg, Elvis Dohmatob, Bertrand Thirion:
FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging. CoRR abs/1512.06999 (2015) - 2014
- [j2]Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux:
Machine learning for neuroimaging with scikit-learn. Frontiers Neuroinformatics 8: 14 (2014) - [i4]Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Alexandre Gramfort, Bertrand Thirion:
Data-driven HRF estimation for encoding and decoding models. CoRR abs/1402.7015 (2014) - [i3]Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux:
Machine Learning for Neuroimaging with Scikit-Learn. CoRR abs/1412.3919 (2014) - 2013
- [c3]Michael Eickenberg, Mehdi Senoussi, Fabian Pedregosa, Alexandre Gramfort, Bertrand Thirion:
Second Order Scattering Descriptors Predict fMRI Activity Due to Visual Textures. PRNI 2013: 5-8 - [c2]Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort:
HRF Estimation Improves Sensitivity of fMRI Encoding and Decoding Models. PRNI 2013: 165-169 - [i2]Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort:
HRF estimation improves sensitivity of fMRI encoding and decoding models. CoRR abs/1305.2788 (2013) - [i1]Michael Eickenberg, Fabian Pedregosa, Senoussi Mehdi, Alexandre Gramfort, Bertrand Thirion:
Second order scattering descriptors predict fMRI activity due to visual textures. CoRR abs/1310.1257 (2013) - 2012
- [j1]Michael Eickenberg, Ryan J. Rowekamp, Minjoon Kouh, Tatyana O. Sharpee:
Characterizing Responses of Translation-Invariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions. Neural Comput. 24(9): 2384-2421 (2012) - [c1]Michael Eickenberg, Alexandre Gramfort, Bertrand Thirion:
Multilayer Scattering Image Analysis Fits fMRI Activity in Visual Areas. PRNI 2012: 37-40
Coauthor Index
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last updated on 2024-10-07 21:17 CEST by the dblp team
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