Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMichael Elad
Person information
- affiliation: Technion - Israel Institute of Technology, Haifa, Israel
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j122]Roy Ganz, Michael Elad:
BIGRoC: Boosting Image Generation via a Robust Classifier. Trans. Mach. Learn. Res. 2023 (2023)- [j121]Bahjat Kawar, Roy Ganz, Michael Elad:
Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance. Trans. Mach. Learn. Res. 2023 (2023) - [i86]Michael Elad, Bahjat Kawar, Gregory Vaksman:
Image Denoising: The Deep Learning Revolution and Beyond - A Survey Paper -. CoRR abs/2301.03362 (2023) - [i85]Guy Bar-Shalom, George Leifman, Michael Elad, Ehud Rivlin:
Weakly-supervised Representation Learning for Video Alignment and Analysis. CoRR abs/2302.04064 (2023) - [i84]Tsachi Blau, Roy Ganz, Chaim Baskin, Michael Elad, Alexander M. Bronstein:
Classifier Robustness Enhancement Via Test-Time Transformation. CoRR abs/2303.15409 (2023) - [i83]George Leifman, Idan Kligvasser, Roman Goldenberg, Michael Elad, Ehud Rivlin:
Colonoscopy Coverage Revisited: Identifying Scanning Gaps in Real-Time. CoRR abs/2305.10026 (2023) - [i82]Idan Kligvasser, George Leifman, Roman Goldenberg, Ehud Rivlin, Michael Elad:
Semi-supervised Quality Evaluation of Colonoscopy Procedures. CoRR abs/2305.10090 (2023) - [i81]Omer Belhasin, Yaniv Romano, Daniel Freedman, Ehud Rivlin, Michael Elad:
Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems. CoRR abs/2305.10124 (2023) - [i80]Bahjat Kawar, Noam Elata, Tomer Michaeli, Michael Elad:
GSURE-Based Diffusion Model Training with Corrupted Data. CoRR abs/2305.13128 (2023) - 2022
- [j120]Aviad Aberdam
, Alona Golts, Michael Elad:
Ada-LISTA: Learned Solvers Adaptive to Varying Models. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9222-9235 (2022) - [c66]Alona Golts, Ido Livneh, Yaniv Zohar, Aaron Ciechanover, Michael Elad:
Simultaneous Detection and Classification of Partially and Weakly Supervised Cells. ECCV Workshops (3) 2022: 313-329 - [c65]Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song:
Denoising Diffusion Restoration Models. NeurIPS 2022 - [i79]Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song:
Denoising Diffusion Restoration Models. CoRR abs/2201.11793 (2022) - [i78]Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex M. Bronstein, Michael Elad:
Threat Model-Agnostic Adversarial Defense using Diffusion Models. CoRR abs/2207.08089 (2022) - [i77]Roy Ganz, Bahjat Kawar, Michael Elad:
Do Perceptually Aligned Gradients Imply Adversarial Robustness? CoRR abs/2207.11378 (2022) - [i76]Bahjat Kawar, Roy Ganz, Michael Elad:
Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance. CoRR abs/2208.08664 (2022) - [i75]Bahjat Kawar, Jiaming Song, Stefano Ermon, Michael Elad:
JPEG Artifact Correction using Denoising Diffusion Restoration Models. CoRR abs/2209.11888 (2022) - [i74]Guy Ohayon, Theo Adrai, Michael Elad, Tomer Michaeli:
Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality. CoRR abs/2211.08944 (2022) - [i73]Gregory Vaksman, Michael Elad:
Patch-Craft Self-Supervised Training for Correlated Image Denoising. CoRR abs/2211.09919 (2022) - [i72]Sean Man, Guy Ohayon, Theo Adrai, Michael Elad:
High-Perceptual Quality JPEG Decoding via Posterior Sampling. CoRR abs/2211.11827 (2022) - [i71]Gilad Kutiel, Regev Cohen, Michael Elad, Daniel Freedman:
What's Behind the Mask: Estimating Uncertainty in Image-to-Image Problems. CoRR abs/2211.15211 (2022) - [i70]Nadav Torem, Roi Ronen, Yoav Y. Schechner, Michael Elad:
Towards A Most Probable Recovery in Optical Imaging. CoRR abs/2212.03235 (2022) - 2021
- [j119]Alona Golts, Daniel Freedman, Michael Elad:
Deep Energy: Task Driven Training of Deep Neural Networks. IEEE J. Sel. Top. Signal Process. 15(2): 324-338 (2021) - [j118]Rajaei Khatib, Dror Simon, Michael Elad:
Learned Greedy Method (LGM): A novel neural architecture for sparse coding and beyond. J. Vis. Commun. Image Represent. 77: 103095 (2021) - [j117]Regev Cohen, Michael Elad, Peyman Milanfar:
Regularization by Denoising via Fixed-Point Projection (RED-PRO). SIAM J. Imaging Sci. 14(3): 1374-1406 (2021) - [j116]Meyer Scetbon, Michael Elad, Peyman Milanfar:
Deep K-SVD Denoising. IEEE Trans. Image Process. 30: 5944-5955 (2021) - [j115]Hossein Talebi Esfandarani, Damien Kelly, Xiyang Luo, Ignacio Garcia-Dorado, Feng Yang, Peyman Milanfar, Michael Elad:
Better Compression With Deep Pre-Editing. IEEE Trans. Image Process. 30: 6673-6685 (2021) - [c64]Xiyang Luo, Hossein Talebi, Feng Yang, Michael Elad, Peyman Milanfar:
The Rate-Distortion-Accuracy Tradeoff: JPEG Case Study. DCC 2021: 354 - [c63]Gregory Vaksman, Michael Elad, Peyman Milanfar:
Patch Craft: Video Denoising by Deep Modeling and Patch Matching. ICCV 2021: 2137-2146 - [c62]Guy Ohayon, Theo Adrai, Gregory Vaksman, Michael Elad, Peyman Milanfar:
High Perceptual Quality Image Denoising with a Posterior Sampling CGAN. ICCVW 2021: 1805-1813 - [c61]Bahjat Kawar, Gregory Vaksman, Michael Elad:
Stochastic Image Denoising by Sampling from the Posterior Distribution. ICCVW 2021: 1866-1875 - [c60]Bahjat Kawar, Gregory Vaksman, Michael Elad:
SNIPS: Solving Noisy Inverse Problems Stochastically. NeurIPS 2021: 21757-21769 - [e4]Yuxin Peng, Shi-Min Hu, Moncef Gabbouj, Kun Zhou, Michael Elad, Kun Xu:
Image and Graphics - 11th International Conference, ICIG 2021, Haikou, China, August 6-8, 2021, Proceedings, Part I. Lecture Notes in Computer Science 12888, Springer 2021, ISBN 978-3-030-87354-7 [contents] - [e3]Yuxin Peng, Shi-Min Hu, Moncef Gabbouj, Kun Zhou, Michael Elad, Kun Xu:
Image and Graphics - 11th International Conference, ICIG 2021, Haikou, China, August 6-8, 2021, Proceedings, Part II. Lecture Notes in Computer Science 12889, Springer 2021, ISBN 978-3-030-87357-8 [contents] - [e2]Yuxin Peng, Shi-Min Hu, Moncef Gabbouj, Kun Zhou, Michael Elad, Kun Xu:
Image and Graphics - 11th International Conference, ICIG 2021, Haikou, China, August 6-8, 2021, Proceedings, Part III. Lecture Notes in Computer Science 12890, Springer 2021, ISBN 978-3-030-87360-8 [contents] - [i69]Bahjat Kawar, Gregory Vaksman, Michael Elad:
Stochastic Image Denoising by Sampling from the Posterior Distribution. CoRR abs/2101.09552 (2021) - [i68]Guy Ohayon, Theo Adrai, Gregory Vaksman, Michael Elad, Peyman Milanfar:
High Perceptual Quality Image Denoising with a Posterior Sampling CGAN. CoRR abs/2103.04192 (2021) - [i67]Gregory Vaksman, Michael Elad, Peyman Milanfar:
Patch Craft: Video Denoising by Deep Modeling and Patch Matching. CoRR abs/2103.13767 (2021) - [i66]Roy Ganz, Michael Elad:
Improved Image Generation via Sparse Modeling. CoRR abs/2104.00464 (2021) - [i65]Bahjat Kawar, Gregory Vaksman, Michael Elad:
SNIPS: Solving Noisy Inverse Problems Stochastically. CoRR abs/2105.14951 (2021) - [i64]Roy Ganz, Michael Elad:
BIGRoC: Boosting Image Generation via a Robust Classifier. CoRR abs/2108.03702 (2021) - 2020
- [j114]Yaniv Romano, Aviad Aberdam, Jeremias Sulam, Michael Elad:
Adversarial Noise Attacks of Deep Learning Architectures: Stability Analysis via Sparse-Modeled Signals. J. Math. Imaging Vis. 62(3): 313-327 (2020) - [j113]Jeremias Sulam, Aviad Aberdam, Amir Beck, Michael Elad:
On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 42(8): 1968-1980 (2020) - [j112]Alona Golts, Daniel Freedman, Michael Elad:
Unsupervised Single Image Dehazing Using Dark Channel Prior Loss. IEEE Trans. Image Process. 29: 2692-2701 (2020) - [j111]Ives Rey-Otero, Jeremias Sulam, Michael Elad:
Variations on the Convolutional Sparse Coding Model. IEEE Trans. Signal Process. 68: 519-528 (2020) - [c59]Gregory Vaksman, Michael Elad, Peyman Milanfar:
LIDIA: Lightweight Learned Image Denoising with Instance Adaptation. CVPR Workshops 2020: 2220-2229 - [i63]Aviad Aberdam, Alona Golts, Michael Elad:
Ada-LISTA: Learned Solvers Adaptive to Varying Models. CoRR abs/2001.08456 (2020) - [i62]Hossein Talebi, Damien Kelly, Xiyang Luo, Ignacio Garcia-Dorado, Feng Yang, Peyman Milanfar, Michael Elad:
Better Compression with Deep Pre-Editing. CoRR abs/2002.00113 (2020) - [i61]Aviad Aberdam, Dror Simon, Michael Elad:
When and How Can Deep Generative Models be Inverted? CoRR abs/2006.15555 (2020) - [i60]Regev Cohen, Michael Elad, Peyman Milanfar:
Regularization by Denoising via Fixed-Point Projection (RED-PRO). CoRR abs/2008.00226 (2020) - [i59]Xiyang Luo, Hossein Talebi, Feng Yang, Michael Elad, Peyman Milanfar:
The Rate-Distortion-Accuracy Tradeoff: JPEG Case Study. CoRR abs/2008.00605 (2020) - [i58]Rajaei Khatib, Dror Simon, Michael Elad:
Learned Greedy Method (LGM): A Novel Neural Architecture for Sparse Coding and Beyond. CoRR abs/2010.07069 (2020)
2010 – 2019
- 2019
- [j110]Tao Hong, Yaniv Romano, Michael Elad:
Acceleration of RED via vector extrapolation. J. Vis. Commun. Image Represent. 63 (2019) - [j109]Aviad Aberdam, Jeremias Sulam, Michael Elad:
Multi-Layer Sparse Coding: The Holistic Way. SIAM J. Math. Data Sci. 1(1): 46-77 (2019) - [j108]Alon Brifman, Yaniv Romano, Michael Elad:
Unified Single-Image and Video Super-Resolution via Denoising Algorithms. IEEE Trans. Image Process. 28(12): 6063-6076 (2019) - [j107]Yael Yankelevsky, Michael Elad:
Finding GEMS: Multi-Scale Dictionaries For High-Dimensional Graph Signals. IEEE Trans. Signal Process. 67(7): 1889-1901 (2019) - [j106]Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad:
MMSE Approximation For Sparse Coding Algorithms Using Stochastic Resonance. IEEE Trans. Signal Process. 67(17): 4597-4610 (2019) - [c58]Ev Zisselman, Jeremias Sulam, Michael Elad:
A Local Block Coordinate Descent Algorithm for the CSC Model. CVPR 2019: 8208-8217 - [c57]Shahar Romem Peled, Yaniv Romano, Michael Elad:
SOS Boosting for Image Deblurring Algorithms. EUSIPCO 2019: 1-5 - [c56]Dror Simon, Michael Elad:
Rethinking the CSC Model for Natural Images. NeurIPS 2019: 2271-2281 - [i57]Gary Mataev, Michael Elad, Peyman Milanfar:
DeepRED: Deep Image Prior Powered by RED. CoRR abs/1903.10176 (2019) - [i56]Dror Simon, Michael Elad:
Rethinking the CSC Model for Natural Images. CoRR abs/1909.05742 (2019) - [i55]Meyer Scetbon, Michael Elad, Peyman Milanfar:
Deep K-SVD Denoising. CoRR abs/1909.13164 (2019) - [i54]Gregory Vaksman, Michael Elad, Peyman Milanfar:
Low-Weight and Learnable Image Denoising. CoRR abs/1911.07167 (2019) - 2018
- [j105]Vardan Papyan, Yaniv Romano, Jeremias Sulam, Michael Elad:
Theoretical Foundations of Deep Learning via Sparse Representations: A Multilayer Sparse Model and Its Connection to Convolutional Neural Networks. IEEE Signal Process. Mag. 35(4): 72-89 (2018) - [j104]Yi Ren, Yaniv Romano, Michael Elad:
Example-Based Image Synthesis via Randomized Patch-Matching. IEEE Trans. Image Process. 27(1): 220-235 (2018) - [j103]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Optimized Pre-Compensating Compression. IEEE Trans. Image Process. 27(10): 4798-4809 (2018) - [j102]Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad:
Multilayer Convolutional Sparse Modeling: Pursuit and Dictionary Learning. IEEE Trans. Signal Process. 66(15): 4090-4104 (2018) - [j101]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Restoration by Compression. IEEE Trans. Signal Process. 66(22): 5833-5847 (2018) - [c55]Yael Yankelevsky, Michael Elad:
Dictionary Learning for High Dimensional Graph Signals. ICASSP 2018: 4669-4673 - [c54]Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad:
Projecting on to the Multi-Layer Convolutional Sparse Coding Model. ICASSP 2018: 6757-6761 - [c53]Yaniv Romano, Michael Elad, Peyman Milanfar:
RED-UCATION: A Novel CNN Architecture Based on Denoising Nonlinearities. ICASSP 2018: 6762-6766 - [c52]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Compression for Multiple Reconstructions. ICIP 2018: 440-444 - [c51]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
System-Aware Compression. ISIT 2018: 2226-2230 - [i53]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
System-Aware Compression. CoRR abs/1801.04853 (2018) - [i52]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Compression for Multiple Reconstructions. CoRR abs/1802.03937 (2018) - [i51]Aviad Aberdam, Jeremias Sulam, Michael Elad:
Multi Layer Sparse Coding: the Holistic Way. CoRR abs/1804.09788 (2018) - [i50]Tao Hong, Yaniv Romano, Michael Elad:
Acceleration of RED via Vector Extrapolation. CoRR abs/1805.02158 (2018) - [i49]Yaniv Romano, Michael Elad:
Classification Stability for Sparse-Modeled Signals. CoRR abs/1805.11596 (2018) - [i48]Alona Golts, Daniel Freedman, Michael Elad:
Deep Energy: Using Energy Functions for Unsupervised Training of DNNs. CoRR abs/1805.12355 (2018) - [i47]Jeremias Sulam, Aviad Aberdam, Michael Elad:
On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks. CoRR abs/1806.00701 (2018) - [i46]Yael Yankelevsky, Michael Elad:
Finding GEMS: Multi-Scale Dictionaries for High-Dimensional Graph Signals. CoRR abs/1806.05356 (2018) - [i45]Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad:
Improving Pursuit Algorithms Using Stochastic Resonance. CoRR abs/1806.10171 (2018) - [i44]Ev Zisselman, Jeremias Sulam, Michael Elad:
A Local Block Coordinate Descent Algorithm for the Convolutional Sparse Coding Model. CoRR abs/1811.00312 (2018) - [i43]Alona Golts, Daniel Freedman, Michael Elad:
Unsupervised Single Image Dehazing Using Dark Channel Prior Loss. CoRR abs/1812.07051 (2018) - 2017
- [j100]Vardan Papyan, Yaniv Romano, Michael Elad:
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding. J. Mach. Learn. Res. 18: 83:1-83:52 (2017) - [j99]Yaniv Romano, Michael Elad, Peyman Milanfar:
The Little Engine That Could: Regularization by Denoising (RED). SIAM J. Imaging Sci. 10(4): 1804-1844 (2017) - [j98]Michael Elad, Peyman Milanfar:
Style Transfer Via Texture Synthesis. IEEE Trans. Image Process. 26(5): 2338-2351 (2017) - [j97]Vardan Papyan, Jeremias Sulam, Michael Elad:
Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding. IEEE Trans. Signal Process. 65(21): 5687-5701 (2017) - [c50]Yael Yankelevsky, Michael Elad:
Structure-aware classification using supervised dictionary learning. ICASSP 2017: 4421-4425 - [c49]Vardan Papyan, Yaniv Romano, Michael Elad, Jeremias Sulam:
Convolutional Dictionary Learning via Local Processing. ICCV 2017: 5306-5314 - [i42]Dmitry Batenkov, Yaniv Romano, Michael Elad:
On the Global-Local Dichotomy in Sparsity Modeling. CoRR abs/1702.03446 (2017) - [i41]Vardan Papyan, Yaniv Romano, Jeremias Sulam, Michael Elad:
Convolutional Dictionary Learning via Local Processing. CoRR abs/1705.03239 (2017) - [i40]Vardan Papyan, Jeremias Sulam, Michael Elad:
Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding. CoRR abs/1707.06066 (2017) - [i39]Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad:
Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning. CoRR abs/1708.08705 (2017) - [i38]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Restoration by Compression. CoRR abs/1711.05147 (2017) - [i37]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Optimized Pre-Compensating Compression. CoRR abs/1711.07901 (2017) - 2016
- [j96]Alona Golts, Michael Elad:
Linearized Kernel Dictionary Learning. IEEE J. Sel. Top. Signal Process. 10(4): 726-739 (2016) - [j95]Arie Rond, Raja Giryes, Michael Elad:
Poisson inverse problems by the Plug-and-Play scheme. J. Vis. Commun. Image Represent. 41: 96-108 (2016) - [j94]Gregory Vaksman, Michael Zibulevsky, Michael Elad:
Patch Ordering as a Regularization for Inverse Problems in Image Processing. SIAM J. Imaging Sci. 9(1): 287-319 (2016) - [j93]Jeremias Sulam, Michael Elad:
Large Inpainting of Face Images With Trainlets. IEEE Signal Process. Lett. 23(12): 1839-1843 (2016) - [j92]Vardan Papyan, Michael Elad:
Multi-Scale Patch-Based Image Restoration. IEEE Trans. Image Process. 25(1): 249-261 (2016) - [j91]Yehuda Dar, Alfred M. Bruckstein, Michael Elad, Raja Giryes:
Postprocessing of Compressed Images via Sequential Denoising. IEEE Trans. Image Process. 25(7): 3044-3058 (2016) - [j90]Yaniv Romano, Michael Elad:
Con-Patch: When a Patch Meets Its Context. IEEE Trans. Image Process. 25(9): 3967-3978 (2016) - [j89]Yael Yankelevsky, Michael Elad:
Dual Graph Regularized Dictionary Learning. IEEE Trans. Signal Inf. Process. over Networks 2(4): 611-624 (2016) - [j88]Jeremias Sulam, Boaz Ophir, Michael Zibulevsky, Michael Elad:
Trainlets: Dictionary Learning in High Dimensions. IEEE Trans. Signal Process. 64(12): 3180-3193 (2016) - [c48]Alon Brifman, Yaniv Romano, Michael Elad:
Turning a denoiser into a super-resolver using plug and play priors. ICIP 2016: 1404-1408 - [c47]Yehuda Dar, Alfred M. Bruckstein, Michael Elad:
Image restoration via successive compression. PCS 2016: 1-5 - [i36]Jeremias Sulam, Boaz Ophir, Michael Zibulevsky, Michael Elad:
Trainlets: Dictionary Learning in High Dimensions. CoRR abs/1602.00212 (2016) - [i35]Gregory Vaksman, Michael Zibulevsky, Michael Elad:
Patch-Ordering as a Regularization for Inverse Problems in Image Processing. CoRR abs/1602.08510 (2016) - [i34]Yaniv Romano, Michael Elad:
Con-Patch: When a Patch Meets its Context. CoRR abs/1603.06812 (2016) - [i33]Amir Adler, David Boublil, Michael Elad, Michael Zibulevsky:
A Deep Learning Approach to Block-based Compressed Sensing of Images. CoRR abs/1606.01519 (2016) - [i32]Vardan Papyan, Jeremias Sulam, Michael Elad:
Working Locally Thinking Globally - Part I: Theoretical Guarantees for Convolutional Sparse Coding. CoRR abs/1607.02005 (2016) - [i31]Vardan Papyan, Jeremias Sulam, Michael Elad:
Working Locally Thinking Globally - Part II: Stability and Algorithms for Convolutional Sparse Coding. CoRR abs/1607.02009 (2016) - [i30]Vardan Papyan, Yaniv Romano, Michael Elad:
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding. CoRR abs/1607.08194 (2016) - [i29]Michael Elad, Peyman Milanfar:
Style-Transfer via Texture-Synthesis. CoRR abs/1609.03057 (2016) - [i28]Yi Ren, Yaniv Romano, Michael Elad:
Example-Based Image Synthesis via Randomized Patch-Matching. CoRR abs/1609.07370 (2016) - [i27]Yael Yankelevsky, Michael Elad:
Structure-Aware Classification using Supervised Dictionary Learning. CoRR abs/1609.09199 (2016) - [i26]Amir Adler, Michael Elad, Michael Zibulevsky:
Compressed Learning: A Deep Neural Network Approach. CoRR abs/1610.09615 (2016) - [i25]Yaniv Romano, Michael Elad, Peyman Milanfar:
The Little Engine that Could: Regularization by Denoising (RED). CoRR abs/1611.02862 (2016) - 2015
- [j87]Javier S. Turek, Michael Elad, Irad Yavneh:
Clutter Mitigation in Echocardiography Using Sparse Signal Separation. Int. J. Biomed. Imaging 2015: 958963:1-958963:18 (2015) - [j86]