Alexandre ABRAHAM
Alexandre ABRAHAM
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Cited by
Cited by
Machine learning for neuroimaging with scikit-learn
A Abraham, F Pedregosa, M Eickenberg, P Gervais, A Mueller, J Kossaifi, ...
Frontiers in neuroinformatics, 14, 2014
Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example
A Abraham, MP Milham, A Di Martino, RC Craddock, D Samaras, ...
NeuroImage 147, 736-745, 2017
Predicting brain-age from multimodal imaging data captures cognitive impairment
F Liem, G Varoquaux, J Kynast, F Beyer, SK Masouleh, JM Huntenburg, ...
Neuroimage 148, 179-188, 2017
Benchmarking functional connectome-based predictive models for resting-state fMRI
K Dadi, M Rahim, A Abraham, D Chyzhyk, M Milham, B Thirion, ...
NeuroImage 192, 115-134, 2019
Offline a/b testing for recommender systems
A Gilotte, C Calauzènes, T Nedelec, A Abraham, S Dollé
Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018
Extracting brain regions from rest fMRI with total-variation constrained dictionary learning
A Abraham, E Dohmatob, B Thirion, D Samaras, G Varoquaux
International conference on medical image computing and computer-assisted …, 2013
Integrating multimodal priors in predictive models for the functional characterization of Alzheimer’s disease
M Rahim, B Thirion, A Abraham, M Eickenberg, E Dohmatob, C Comtat, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2015
Region segmentation for sparse decompositions: better brain parcellations from rest fMRI
A Abraham, E Dohmatob, B Thirion, D Samaras, G Varoquaux
arXiv preprint arXiv:1412.3925, 2014
Comparing functional connectivity based predictive models across datasets
K Dadi, A Abraham, M Rahim, B Thirion, G Varoquaux
2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI), 1-4, 2016
Loading and plotting of cortical surface representations in Nilearn
J Huntenburg, A Abraham, J Loula, F Liem, K Dadi, G Varoquaux
Research Ideas and Outcomes 3, e12342, 2017
Rebuilding trust in active learning with actionable metrics
A Abraham, L Dreyfus-Schmidt
2020 International Conference on Data Mining Workshops (ICDMW), 836-843, 2020
Learning functional brain atlases modeling inter-subject variability
A Abraham
Université Paris-Saclay, 2015
Sample Noise Impact on Active Learning
A Abraham, L Dreyfus-Schmidt
arXiv preprint arXiv:2109.01372, 2021
Cardinal, a metric-based Active learning framework
A Abraham, L Dreyfus-Schmidt
Software Impacts 12, 100250, 2022
An in silico drug repurposing pipeline to identify drugs with the potential to inhibit SARS-CoV-2 replication
M MacMahon, W Hwang, S Yim, E MacMahon, A Abraham, J Barton, ...
Towards Clear Expectations for Uncertainty Estimation
V Bouvier, S Maggio, A Abraham, L Dreyfus-Schmidt
arXiv preprint arXiv:2207.13341, 2022
Identification and validation of Triamcinolone and Gallopamil as treatments for early COVID-19 via an in silico repurposing pipeline
M MacMahon, W Hwang, S Yim, E MacMahon, A Abraham, J Barton, ...
arXiv preprint arXiv:2107.02905, 2021
Morphology on color images
A Abraham
Topological Watershed
A Abraham
Les nouveautés de HAL v3. 0 de A à Z (13/02/15)
M Rahim, B Thirion, A Abraham, M Eickenberg, E Dohmatob
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