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Alex Fedorov
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Learning deep representations by mutual information estimation and maximization
RD Hjelm, A Fedorov, S Lavoie-Marchildon, K Grewal, P Bachman, ...
arXiv preprint arXiv:1808.06670, 2018
19152018
Deep attention recurrent Q-network
I Sorokin, A Seleznev, M Pavlov, A Fedorov, A Ignateva
arXiv preprint arXiv:1512.01693, 2015
1462015
Deep residual learning for neuroimaging: An application to predict progression to alzheimer’s disease
A Abrol, M Bhattarai, A Fedorov, Y Du, S Plis, V Calhoun, ...
Journal of neuroscience methods 339, 108701, 2020
862020
Group ICA for identifying biomarkers in schizophrenia:‘Adaptive’networks via spatially constrained ICA show more sensitivity to group differences than spatio-temporal regression
MS Salman, Y Du, D Lin, Z Fu, A Fedorov, E Damaraju, J Sui, J Chen, ...
NeuroImage: Clinical 22, 101747, 2019
662019
End-to-end learning of brain tissue segmentation from imperfect labeling
A Fedorov, J Johnson, E Damaraju, A Ozerin, V Calhoun, S Plis
2017 International Joint Conference on Neural Networks (IJCNN), 3785-3792, 2017
362017
Prediction of Progression to Alzheimer's disease with Deep InfoMax
A Fedorov, RD Hjelm, A Abrol, Z Fu, Y Du, S Plis, VD Calhoun
2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2019
212019
Whole MILC: generalizing learned dynamics across tasks, datasets, and populations
U Mahmood, MM Rahman, A Fedorov, N Lewis, Z Fu, VD Calhoun, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
172020
Almost instant brain atlas segmentation for large-scale studies
A Fedorov, E Damaraju, V Calhoun, S Plis
arXiv preprint arXiv:1711.00457, 2017
142017
On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer’s Disease
A Fedorov, L Wu, T Sylvain, M Luck, TP DeRamus, D Bleklov, SM Plis, ...
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1548-1552, 2021
112021
Transfer Learning of fMRI Dynamics
U Mahmood, MM Rahman, A Fedorov, Z Fu, S Plis
arXiv preprint arXiv:1911.06813, 2019
82019
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer’s Disease
A Fedorov, T Sylvain, E Geenjaar, M Luck, L Wu, TP DeRamus, A Kirilin, ...
2021 IEEE 9th International Conference on Healthcare Informatics (ICHI), 23-30, 2021
4*2021
Learnt dynamics generalizes across tasks, datasets, and populations
U Mahmood, MM Rahman, A Fedorov, Z Fu, VD Calhoun, SM Plis
arXiv preprint arXiv:1912.03130, 2019
42019
Interpreting models interpreting brain dynamics
M Rahman, U Mahmood, N Lewis, H Gazula, A Fedorov, Z Fu, ...
Scientific Reports 12 (1), 1-15, 2022
32022
Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data
A Fedorov, E Geenjaar, L Wu, TP DeRamus, VD Calhoun, SM Plis
arXiv preprint arXiv:2103.15914, 2021
22021
Pipeline-Invariant Representation Learning for Neuroimaging
X Li, A Fedorov, M Mathur, A Abrol, G Kiar, S Plis, V Calhoun
arXiv preprint arXiv:2208.12909, 2022
12022
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes
A Fedorov, E Geenjaar, L Wu, T Sylvain, TP DeRamus, M Luck, M Misiura, ...
arXiv preprint arXiv:2209.02876, 2022
2022
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