Andrés Hoyos-Idrobo
Andrés Hoyos-Idrobo
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TitleCited byYear
Assessing and tuning brain decoders: cross-validation, caveats, and guidelines
G Varoquaux, PR Raamana, DA Engemann, A Hoyos-Idrobo, Y Schwartz, ...
NeuroImage 145, 166-179, 2017
1842017
On variant strategies to solve the magnitude least squares optimization problem in parallel transmission pulse design and under strict SAR and power constraints
A Hoyos-Idrobo, P Weiss, A Massire, A Amadon, N Boulant
IEEE transactions on medical imaging 33 (3), 739-748, 2013
592013
Improving sparse recovery on structured images with bagged clustering
A Hoyos-Idrobo, Y Schwartz, G Varoquaux, B Thirion
2015 International Workshop on Pattern Recognition in NeuroImaging, 73-76, 2015
122015
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signals
A Hoyos-Idrobo, G Varoquaux, J Kahn, B Thirion
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018
82018
FReM–scalable and stable decoding with fast regularized ensemble of models
A Hoyos-Idrobo, G Varoquaux, Y Schwartz, B Thirion
NeuroImage 180, 160-172, 2018
62018
Towards a faster randomized parcellation based inference
A Hoyos-Idrobo, G Varoquaux, B Thirion
2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI), 1-4, 2017
12017
Fast clustering for scalable statistical analysis on structured images
B Thirion, A Hoyos-Idrobo, J Kahn, G Varoquaux
arXiv preprint arXiv:1511.04898, 2015
12015
Local Bures-Wasserstein Transport: A Practical and Fast Mapping Approximation
A Hoyos-Idrobo
arXiv preprint arXiv:1906.08227, 2019
2019
Gaussian Processes for HRF estimation for BOLD fMRI
M Eickenberg, A Frau-Pascual, A Hoyos-Idrobo
arXiv preprint arXiv:1708.09762, 2017
2017
Ensembles of models in fMRI: stable learning in large-scale settings
A Hoyos-Idrobo
2017
Fast brain decoding with random sampling and random projections
A Hoyos-Idrobo, G Varoquaux, B Thirion
Pattern Recognition in NeuroImaging (PRNI), 2016 International Workshop on, 2016
2016
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Articles 1–11