Deep-learning tomography M Araya-Polo, J Jennings, A Adler, T Dahlke The Leading Edge 37 (1), 58-66, 2018 | 539 | 2018 |
Audio inpainting A Adler, V Emiya, MG Jafari, M Elad, R Gribonval, MD Plumbley IEEE Transactions on Audio, Speech, and Language Processing 20 (3), 922-932, 2011 | 304 | 2011 |
Sparse coding with anomaly detection A Adler, M Elad, Y Hel-Or, E Rivlin Journal of Signal Processing Systems 79 (2), 179-188, 2015 | 139 | 2015 |
Deep learning for seismic inverse problems: Toward the acceleration of geophysical analysis workflows A Adler, M Araya-Polo, T Poggio IEEE Signal Processing Magazine 38 (2), 89-119, 2021 | 108 | 2021 |
Compressed learning: A deep neural network approach A Adler, M Elad, M Zibulevsky Signal Processing with Adaptive Sparse Structured Representations (SPARS) 2017, 2017 | 98 | 2017 |
A constrained matching pursuit approach to audio declipping A Adler, V Emiya, MG Jafari, M Elad, R Gribonval, MD Plumbley 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 85 | 2011 |
A deep learning approach to block-based compressed sensing of images A Adler, D Boublil, M Elad, M Zibulevsky arXiv preprint arXiv:1606.01519, 2016 | 70 | 2016 |
Block-based compressed sensing of images via deep learning A Adler, D Boublil, M Zibulevsky IEEE 19th International Workshop on Multimedia Signal Processing (MMSP), 1-6, 2017 | 68 | 2017 |
Compressed learning for image classification: A deep neural network approach E Zisselman, A Adler, M Elad Handbook of Numerical Analysis 19, 3-17, 2018 | 58 | 2018 |
Linear-Time Subspace Clustering via Bipartite Graph Modeling A Adler, M Elad, Y Hel-Or IEEE Transactions on Neural Networks and Learning Systems 26 (10), 2234 - 2246, 2015 | 48 | 2015 |
Detection of the number of signals by signal subspace matching M Wax, A Adler IEEE Transactions on Signal Processing 69, 973-985, 2021 | 44 | 2021 |
Probabilistic subspace clustering via sparse representations A Adler, M Elad, Y Hel-Or IEEE Signal Processing Letters 20 (1), 63-66, 2012 | 44 | 2012 |
Towards hate speech detection at large via deep generative modeling T Wullach, A Adler, E Minkov IEEE Internet Computing 25 (2), 48-57, 2020 | 41 | 2020 |
A shrinkage learning approach for single image super-resolution with overcomplete representations A Adler, Y Hel-Or, M Elad European Conference on Computer Vision (ECCV), 622-635, 2010 | 41 | 2010 |
Deep recurrent architectures for seismic tomography A Adler, M Araya-Polo, T Poggio 81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019 | 33 | 2019 |
Fast and accurate seismic tomography via deep learning M Araya-Polo, A Adler, S Farris, J Jennings Deep learning: Algorithms and applications, 129-156, 2020 | 31 | 2020 |
Fight fire with fire: Fine-tuning hate detectors using large samples of generated hate speech T Wullach, A Adler, E Minkov Findings of the Association for Computational Linguistics: EMNLP 2021, 4699–4705, 2021 | 29 | 2021 |
MEG source localization via deep learning D Pantazis, A Adler Sensors 21 (13), 4278, 2021 | 23 | 2021 |
Detection of the number of signals in uniform arrays by invariant-signal-subspace matching M Wax, A Adler IEEE Transactions on Signal Processing 70, 1270-1281, 2022 | 19 | 2022 |
A weighted discriminative approach for image denoising with overcomplete representations A Adler, Y Hel-Or, M Elad 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 15 | 2010 |