| Orange: data mining toolbox in Python J Demšar, T Curk, A Erjavec, Č Gorup, T Hočevar, M Milutinovič, ... the Journal of machine Learning research 14 (1), 2349-2353, 2013 | 2621 | 2013 |
| Barlow twins: Self-supervised learning via redundancy reduction J Zbontar, L Jing, I Misra, Y LeCun, S Deny International conference on machine learning, 12310-12320, 2021 | 2479 | 2021 |
| Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches J Žbontar, Y LeCun The Journal of Machine Learning Research 17 (65), 1-32, 2016 | 1620 | 2016 |
| Computing the stereo matching cost with a convolutional neural network J Zbontar, Y LeCun Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 967 | 2015 |
| fastMRI: An Open Dataset and Benchmarks for Accelerated MRI J Zbontar, F Knoll, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, ... arXiv preprint arXiv:1811.08839, 2018 | 921 | 2018 |
| fastMRI: A publicly available raw k-space and DICOM dataset of knee images for accelerated MR image reconstruction using machine learning F Knoll, J Zbontar, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, ... Radiology: Artificial Intelligence 2 (1), e190007, 2020 | 394 | 2020 |
| End-to-end variational networks for accelerated MRI reconstruction A Sriram, J Zbontar, T Murrell, A Defazio, CL Zitnick, N Yakubova, F Knoll, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 328 | 2020 |
| Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge F Knoll, T Murrell, A Sriram, N Yakubova, J Zbontar, M Rabbat, A Defazio, ... Magnetic resonance in medicine 84 (6), 3054-3070, 2020 | 226 | 2020 |
| Using deep learning to accelerate knee MRI at 3 T: results of an interchangeability study MP Recht, J Zbontar, DK Sodickson, F Knoll, N Yakubova, A Sriram, ... American Journal of Roentgenology 215 (6), 1421-1429, 2020 | 143 | 2020 |
| GrappaNet: Combining parallel imaging with deep learning for multi-coil MRI reconstruction A Sriram, J Zbontar, T Murrell, CL Zitnick, A Defazio, DK Sodickson Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 118 | 2020 |
| Improving the speed of MRI with artificial intelligence PM Johnson, MP Recht, F Knoll Seminars in musculoskeletal radiology 24 (01), 012-020, 2020 | 74 | 2020 |
| Implicit rank-minimizing autoencoder L Jing, J Zbontar Advances in Neural Information Processing Systems 33, 14736-14746, 2020 | 56 | 2020 |
| Deep learning reconstruction enables prospectively accelerated clinical knee MRI PM Johnson, DJ Lin, J Zbontar, CL Zitnick, A Sriram, M Muckley, JS Babb, ... Radiology 307 (2), e220425, 2023 | 53 | 2023 |
| Simulating single-coil MRI from the responses of multiple coils M Tygert, J Zbontar Communications in Applied Mathematics and Computational Science 15 (2), 115-127, 2020 | 24 | 2020 |
| Fast incremental learning for off-road robot navigation A Provodin, L Torabi, B Flepp, Y LeCun, M Sergio, LD Jackel, U Muller, ... arXiv preprint arXiv:1606.08057, 2016 | 10 | 2016 |
| Short answer scoring by stacking J Zbontar ASAP Short Answer Scoring Competition System Description. Retrieved July 28 …, 2012 | 8 | 2012 |
| Compressed sensing with a jackknife and a bootstrap M Tygert, R Ward, J Zbontar arXiv preprint arXiv:1809.06959, 2018 | 6 | 2018 |
| Compressed sensing with a Jackknife, a bootstrap, and visualization A Defazio, M Tygert, R Ward, J Zbontar J Data Sci Stat Vis 2 (4), 2022 | 4 | 2022 |
| An evaluation of machine learning methods for prominence detection in French J Demsar, T Curk, A Erjavec, C Gorup, T Hocevar, M Milutinovic, ... J. Mach. Learn. Res 14, 2349-2353, 2013 | 4 | 2013 |
| Team ULjubljana’s Solution to the JRS 2012 Data Mining Competition J Žbontar, M Zitnik, M Zidar, G Majcen, M Potocnik, B Zupan Rough Sets and Current Trends in Computing, 471--478, 2012 | 3 | 2012 |
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityEmail verificata su cs.nyu.edu