| Explainability methods for graph convolutional neural networks PE Pope, S Kolouri, M Rostami, CE Martin, H Hoffmann Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 588 | 2019 |
| Deep transfer learning for few-shot SAR image classification M Rostami, S Kolouri, E Eaton, K Kim Remote Sensing 11 (11), 1374, 2019 | 234 | 2019 |
| Using Task Features for Zero-Shot Knowledge Transfer in Lifelong Learning. D Isele, M Rostami, E Eaton IJCAI 16, 1620-1626, 2016 | 109 | 2016 |
| SSIM-inspired image restoration using sparse representation A Rehman, M Rostami, Z Wang, D Brunet, ER Vrscay EURASIP Journal on Advances in Signal Processing 2012, 1-12, 2012 | 102 | 2012 |
| Complementary learning for overcoming catastrophic forgetting using experience replay M Rostami, S Kolouri, PK Pilly IJCAI 19, 3339-3345, 2019 | 77 | 2019 |
| Unsupervised model adaptation for continual semantic segmentation S Stan, M Rostami Proceedings of the AAAI conference on artificial intelligence 35 (3), 2593-2601, 2021 | 72 | 2021 |
| Image deblurring using derivative compressed sensing for optical imaging application M Rostami, O Michailovich, Z Wang IEEE transactions on image processing 21 (7), 3139-3149, 2012 | 71 | 2012 |
| Sar image classification using few-shot cross-domain transfer learning M Rostami, S Kolouri, E Eaton, K Kim Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 67 | 2019 |
| Lifelong domain adaptation via consolidated internal distribution M Rostami Advances in neural information processing systems 34, 11172-11183, 2021 | 65 | 2021 |
| Climb: A continual learning benchmark for vision-and-language tasks T Srinivasan, TY Chang, L Pinto Alva, G Chochlakis, M Rostami, ... Advances in Neural Information Processing Systems 35, 29440-29453, 2022 | 56 | 2022 |
| Generative continual concept learning M Rostami, S Kolouri, P Pilly, J McClelland Proceedings of the AAAI conference on artificial intelligence 34 (04), 5545-5552, 2020 | 51 | 2020 |
| Objective quality assessment of interpolated natural images H Yeganeh, M Rostami, Z Wang IEEE Transactions on Image Processing 24 (11), 4651-4663, 2015 | 48 | 2015 |
| Learn continually, generalize rapidly: Lifelong knowledge accumulation for few-shot learning X Jin, BY Lin, M Rostami, X Ren Findings of the Association for Computational Linguistics: EMNLP, 2021 | 42 | 2021 |
| Privacy preserving domain adaptation for semantic segmentation of medical images S Stan, M Rostami British Machine Vision Conference, 2022 | 40* | 2022 |
| One-shot learning for temporal knowledge graphs M Mirtaheri, M Rostami, X Ren, F Morstatter, A Galstyan Proceeding of Automated Knowledge Base Construction, 2021 | 38 | 2021 |
| Detection and continual learning of novel face presentation attacks M Rostami, L Spinoulas, M Hussein, J Mathai, W Abd-Almageed Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 38 | 2021 |
| A crowdsourcing triage algorithm for geopolitical event forecasting M Rostami, D Huber, TC Lu Proceedings of the 12th ACM Conference on Recommender Systems, 377-381, 2018 | 38 | 2018 |
| Objective quality assessment for image super-resolution: A natural scene statistics approach H Yeganeh, M Rostami, Z Wang 2012 19th IEEE International Conference on Image Processing, 1481-1484, 2012 | 38 | 2012 |
| Using task descriptions in lifelong machine learning for improved performance and zero-shot transfer M Rostami, D Isele, E Eaton Journal of Artificial Intelligence Research 67, 673-704, 2020 | 37 | 2020 |
| Multi-agent distributed lifelong learning for collective knowledge acquisition M Rostami, S Kolouri, K Kim, E Eaton Proceedings of the 17th International Conference on Autonomous Agents and …, 2018 | 36 | 2018 |
