| Sequence-to-sequence contrastive learning for text recognition A Aberdam, R Litman, S Tsiper, O Anschel, R Slossberg, S Mazor, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 121 | 2021 |
| On multi-layer basis pursuit, efficient algorithms and convolutional neural networks J Sulam, A Aberdam, A Beck, M Elad IEEE transactions on pattern analysis and machine intelligence 42 (8), 1968-1980, 2019 | 104 | 2019 |
| Ada-lista: Learned solvers adaptive to varying models A Aberdam, A Golts, M Elad IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 9222 …, 2021 | 38 | 2021 |
| Multi-Layer Sparse Coding: The Holistic Way A Aberdam, J Sulam, M Elad SIAM Journal on Mathematics of Data Science, 2019, 2018 | 35 | 2018 |
| Adversarial noise attacks of deep learning architectures: Stability analysis via sparse-modeled signals Y Romano, A Aberdam, J Sulam, M Elad Journal of Mathematical Imaging and Vision 62, 313-327, 2020 | 26 | 2020 |
| Barycenters of natural images constrained wasserstein barycenters for image morphing D Simon, A Aberdam Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 24 | 2020 |
| Multimodal semi-supervised learning for text recognition A Aberdam, R Ganz, S Mazor, R Litman arXiv preprint arXiv:2205.03873, 2022 | 22 | 2022 |
| Out-of-vocabulary challenge report S Garcia-Bordils, A Mafla, AF Biten, O Nuriel, A Aberdam, S Mazor, ... European Conference on Computer Vision, 359-375, 2022 | 17 | 2022 |
| Another step toward demystifying deep neural networks M Elad, D Simon, A Aberdam Proceedings of the National Academy of Sciences 117 (44), 27070-27072, 2020 | 13 | 2020 |
| When and how can deep generative models be inverted? A Aberdam, D Simon, M Elad arXiv preprint arXiv:2006.15555, 2020 | 13 | 2020 |
| Clipter: Looking at the bigger picture in scene text recognition A Aberdam, D Bensaïd, A Golts, R Ganz, O Nuriel, R Tichauer, S Mazor, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 11 | 2023 |
| Towards models that can see and read R Ganz, O Nuriel, A Aberdam, Y Kittenplon, S Mazor, R Litman Proceedings of the IEEE/CVF international conference on computer vision …, 2023 | 10 | 2023 |
| On calibration of scene-text recognition models R Slossberg, O Anschel, A Markovitz, R Litman, A Aberdam, S Tsiper, ... European Conference on Computer Vision, 263-279, 2022 | 10 | 2022 |
| An accelerated coordinate gradient descent algorithm for non-separable composite optimization A Aberdam, A Beck Journal of Optimization Theory and Applications 193 (1), 219-246, 2022 | 7 | 2022 |
| Question aware vision transformer for multimodal reasoning R Ganz, Y Kittenplon, A Aberdam, E Ben Avraham, O Nuriel, S Mazor, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 3 | 2024 |
| GRAM: Global reasoning for multi-page VQA T Blau, S Fogel, R Ronen, A Golts, R Ganz, E Ben Avraham, A Aberdam, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
| Deep-Learning-Based Classification of Cyclic-Alternating-Pattern Sleep Phases Y Kahana, A Aberdam, A Amar, I Cohen Entropy 25 (10), 1395, 2023 | 1 | 2023 |
| Deep Learning as Sparsity-Enforcing Algorithms A Aberdam, J Sulam Mathematical Aspects of Deep Learning, 314, 2022 | | 2022 |
| 2020 Index IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 42 A Aberdam, J Achterhold, JK Adams, E Adeli, S Agaian, K Aizawa, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (1), 2021 | | 2021 |
| Spatial-temporal plane-wave image formation with Sparse Uniform ReSampling T Chernyakova, A Aberdam, E Bar-Ilan, Y Eldar 2017 IEEE International Ultrasonics Symposium (IUS), 1-1, 2017 | | 2017 |
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