| 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 | 1915 | 2018 |
| Deep attention recurrent Q-network I Sorokin, A Seleznev, M Pavlov, A Fedorov, A Ignateva arXiv preprint arXiv:1512.01693, 2015 | 146 | 2015 |
| 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 | 86 | 2020 |
| 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 | 66 | 2019 |
| 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 | 36 | 2017 |
| 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 | 21 | 2019 |
| 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 | 17 | 2020 |
| Almost instant brain atlas segmentation for large-scale studies A Fedorov, E Damaraju, V Calhoun, S Plis arXiv preprint arXiv:1711.00457, 2017 | 14 | 2017 |
| 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 | 11 | 2021 |
| Transfer Learning of fMRI Dynamics U Mahmood, MM Rahman, A Fedorov, Z Fu, S Plis arXiv preprint arXiv:1911.06813, 2019 | 8 | 2019 |
| 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 | 4 | 2019 |
| Interpreting models interpreting brain dynamics M Rahman, U Mahmood, N Lewis, H Gazula, A Fedorov, Z Fu, ... Scientific Reports 12 (1), 1-15, 2022 | 3 | 2022 |
| 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 | 2 | 2021 |
| 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 | 1 | 2022 |
| 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 |
Vince D. CalhounDirector-Translational Research in Neuroimaging and Data Science (TReNDS;GSU/GAtech/Emory)Verified email at gsu.edu
