| 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 | 101 | 2018 |
| Deep attention recurrent Q-network I Sorokin, A Seleznev, M Pavlov, A Fedorov, A Ignateva arXiv preprint arXiv:1512.01693, 2015 | 47 | 2015 |
| 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 | 11 | 2017 |
| 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 | 6 | 2019 |
| Almost instant brain atlas segmentation for large-scale studies A Fedorov, E Damaraju, V Calhoun, S Plis arXiv preprint arXiv:1711.00457, 2017 | 6 | 2017 |
| 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 bioRxiv, 470252, 2019 | 3 | 2019 |
| 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 | 2 | 2019 |
| Transfer Learning of fMRI Dynamics U Mahmood, MM Rahman, A Fedorov, Z Fu, S Plis arXiv preprint arXiv:1911.06813, 2019 | | 2019 |
