Publications Journal Papers

Deep Learning

M. Scetbon, M. Elad, and P. Milanfar, Deep K-SVD Denoising, submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence. software
A. Golts, D. Freedman, and M. Elad, Deep-Energy: Unsupervised Training of Deep Neural Networks, submitted to IEEE Transactions on Image Processing. software
J. Sulam, A. Aberdam, A. Beck, and M. Elad, On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), March 2019.
A. Golts, D. Freedman, and M. Elad, Unsupervised Single Image Dehazing Using Dark Channel Prior Loss, submitted to IEEE Transactions on Image Processing. software
A. Aberdam, J. Sulam, and M. Elad, Multi Layer Sparse Coding: the Holistic Way, SIAM Journal on Mathematics of Data Science (SIMODS), Vol. 1, No. 1, Pages 46-77, February 2019. software
Y. Romano, A. Aberdam, J. Sulam, and M. Elad, Adversarial Noise Attacks of Deep Learning Architectures – Stability Analysis via Sparse Modeled Signals, to appear in Journal of Mathematical Imaging and Vision (Special issue on Mathematical Foundations of Deep Learning in Imaging Sciences).
J. Sulam, V. Papyan, Y. Romano, and M. Elad, Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning, IEEE Trans. on Signal Processing, Vol. 66, No. 15, Pages 4090-4104, August 2018.
V. Papyan, Y. Romano, J. Sulam, and M. Elad, Theoretical Foundations of Deep Learning via Sparse Representations, IEEE Signal Processing Magazine, Vol. 35, No. 4, Pages 72-89, June 2018.
V. Papyan, Y. Romano, and M. Elad, Convolutional Neural Networks Analyzed via Convolutional Sparse Coding, Journal of Machine Learning Research, Vol. 18, Pages 1-52, July 2017.
D. Boublil, M. Elad, J. Shtok, and M. Zibulevsky, Spatially-Adaptive Reconstruction in Computed Tomography using Neural Networks, IEEE Transactions on Medical Imaging, Vol. 34, No. 7, Pages 1474-1485, July 2015.
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