Yaniv Romano

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Michael EladProfessor of Computer Science, Technion, Israel確認したメールアドレス: cs.technion.ac.il
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford University確認したメールアドレス: stanford.edu
Matteo SesiaUniversity of Southern California確認したメールアドレス: usc.edu
Jeremias SulamAssistant Professor, BME, Johns Hopkins University確認したメールアドレス: jhu.edu
Vardan PapyanAssistant Professor, University of Toronto確認したメールアドレス: utoronto.ca
Stephen BatesAssistant Professor, MIT EECS確認したメールアドレス: cs.berkeley.edu
Peyman MilanfarDistinguished Scientist, Google確認したメールアドレス: google.com
Shai Feldman確認したメールアドレス: cs.technion.ac.il
Anastasios Nikolas AngelopoulosPh.D. Student, UC Berkeley確認したメールアドレス: berkeley.edu
Evan PattersonTopos Institute確認したメールアドレス: epatters.org
LIHUA LEIStanford University確認したメールアドレス: stanford.edu
Chiara SabattiProfessor of Biomedical Data Science and of Statistics, Stanford University確認したメールアドレス: stanford.edu
Asaf GendlerMaster graduate from the ECE Faculty, Technion, Israel Institute of Technology確認したメールアドレス: campus.technion.ac.il
Matan ProtterBigPanda確認したメールアドレス: bigpanda.io
Shalev ShaerPhD candidate, Technion, Israel確認したメールアドレス: campus.technion.ac.il
Srigokul UpadhyayulaUniversity of California, Berkeley確認したメールアドレス: berkeley.edu
Thayer AlshaabiHoward Hughes Medical Institute, University of California, Berkeley確認したメールアドレス: berkeley.edu
Amit Pal Singh KohliPhD Candidate, University of California, Berkeley確認したメールアドレス: berkeley.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley確認したメールアドレス: cs.berkeley.edu
Tsui-Wei WengUCSD確認したメールアドレス: ucsd.edu

フォロー

Yaniv Romano

Assistant Professor of Electrical Engineering and Computer Science, Technion, Israel

確認したメールアドレス: technion.ac.il - ホームページ

Machine Learning Statistics Deep Learning Sparse Representations Inverse Problems


タイトル引用回数順公開年順タイトル順	引用先引用先	年
The little engine that could: Regularization by denoising (RED) Y Romano, M Elad, P Milanfar SIAM Journal on Imaging Sciences 10 (4), 1804-1844, 2017	848	2017
Conformalized quantile regression Y Romano, E Patterson, E Candes Advances in neural information processing systems 32, 2019	568	2019
RAISR: rapid and accurate image super resolution Y Romano, J Isidoro, P Milanfar IEEE Transactions on Computational Imaging 3 (1), 110-125, 2016	338	2016
Convolutional neural networks analyzed via convolutional sparse coding V Papyan, Y Romano, M Elad Journal of Machine Learning Research 18 (83), 1-52, 2017	323	2017
Classification with valid and adaptive coverage Y Romano, M Sesia, E Candes Advances in Neural Information Processing Systems 33, 3581-3591, 2020	258	2020
Convolutional dictionary learning via local processing V Papyan, Y Romano, J Sulam, M Elad Proceedings of the IEEE International Conference on Computer Vision, 5296-5304, 2017	165	2017
Deep knockoffs Y Romano, M Sesia, E Candès Journal of the American Statistical Association 115 (532), 1861-1872, 2020	162	2020
Boosting of Image Denoising Algorithms Y Romano, M Elad arXiv preprint arXiv:1502.06220, 2015	160	2015
Single image interpolation via adaptive nonlocal sparsity-based modeling Y Romano, M Protter, M Elad IEEE Transactions on Image Processing 23 (7), 3085-3098, 2014	150	2014
Theoretical foundations of deep learning via sparse representations: A multilayer sparse model and its connection to convolutional neural networks V Papyan, Y Romano, J Sulam, M Elad IEEE Signal Processing Magazine 35 (4), 72-89, 2018	149	2018
Multilayer convolutional sparse modeling: Pursuit and dictionary learning J Sulam, V Papyan, Y Romano, M Elad IEEE Transactions on Signal Processing 66 (15), 4090-4104, 2018	146	2018
Testing for outliers with conformal p-values S Bates, E Candès, L Lei, Y Romano, M Sesia The Annals of Statistics 51 (1), 149-178, 2023	127	2023
Turning a denoiser into a super-resolver using plug and play priors A Brifman, Y Romano, M Elad 2016 IEEE International Conference on Image Processing (ICIP), 1404-1408, 2016	110	2016
Image-to-image regression with distribution-free uncertainty quantification and applications in imaging AN Angelopoulos, AP Kohli, S Bates, M Jordan, J Malik, T Alshaabi, ... International Conference on Machine Learning, 717-730, 2022	84	2022
With malice toward none: Assessing uncertainty via equalized coverage Y Romano, RF Barber, C Sabatti, E Candès Harvard Data Science Review 2 (2), 4, 2020	78	2020
Conformal prediction using conditional histograms M Sesia, Y Romano Advances in Neural Information Processing Systems 34, 6304-6315, 2021	65	2021
Improving K-SVD denoising by post-processing its method-noise Y Romano, M Elad 2013 IEEE International Conference on Image Processing, 435-439, 2013	47	2013
Unified single-image and video super-resolution via denoising algorithms A Brifman, Y Romano, M Elad IEEE Transactions on Image Processing 28 (12), 6063-6076, 2019	45	2019
Achieving equalized odds by resampling sensitive attributes Y Romano, S Bates, E Candes Advances in neural information processing systems 33, 361-371, 2020	43	2020
Training uncertainty-aware classifiers with conformalized deep learning BS Einbinder, Y Romano, M Sesia, Y Zhou Advances in Neural Information Processing Systems 35, 22380-22395, 2022	41	2022

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