Michael Eickenberg
According to our database1,
Michael Eickenberg
authored at least 51 papers
between 2012 and 2024.
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Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
Trans. Mach. Learn. Res., 2024
CoRR, 2024
From Feature Visualization to Visual Circuits: Effect of Adversarial Model Manipulation.
CoRR, 2024
CoRR, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Mach. Learn. Sci. Technol., March, 2023
Proceedings of the International Conference on Machine Learning, 2023
2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence.
CoRR, 2021
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning.
CoRR, 2021
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging.
Proceedings of the Mathematical and Scientific Machine Learning, 2021
Arrhythmia Classification of Reduced-Lead Electrocardiograms by Scattering-Recurrent Networks.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021
2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Arrhythmia Classification of 12-lead Electrocardiograms by Hybrid Scattering-LSTM Networks.
Proceedings of the Computing in Cardiology, 2020
2019
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
2017
Seeing it all: Convolutional network layers map the function of the human visual system.
NeuroImage, 2017
ERCIM News, 2017
Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging.
Proceedings of the Information Processing in Medical Imaging, 2017
2016
PLoS Comput. Biol., 2016
Local Q-linear convergence and finite-time active set identification of ADMM on a class of penalized regression problems.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
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).
PhD thesis, 2015
FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging.
CoRR, 2015
Speeding-Up Model-Selection in Graphnet via Early-Stopping and Univariate Feature-Screening.
Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015
Grouping Total Variation and Sparsity: Statistical Learning with Segmenting Penalties.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015
2014
Frontiers Neuroinformatics, 2014
2013
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013
2012
Characterizing Responses of Translation-Invariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions.
Neural Comput., 2012
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012