| PILOT: Physics-informed learned optimal trajectories for accelerated MRI T Weiss, O Senouf, S Vedula, O Michailovich, M Zibulevsky, A Bronstein Journal of Machine Learning for Biomedical Imaging (MELBA), 2021 | 90* | 2021 |
| Towards CT-quality ultrasound imaging using deep learning S Vedula, O Senouf, AM Bronstein, OV Michailovich, M Zibulevsky arXiv preprint arXiv:1710.06304, 2017 | 48 | 2017 |
| Self-supervised learning of inverse problem solvers in medical imaging O Senouf, S Vedula, T Weiss, A Bronstein, O Michailovich, M Zibulevsky Domain Adaptation and Representation Transfer and Medical Image Learning …, 2019 | 37 | 2019 |
| High frame-rate cardiac ultrasound imaging with deep learning O Senouf, S Vedula, G Zurakhov, A Bronstein, M Zibulevsky, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 36 | 2018 |
| Joint learning of Cartesian undersampling and reconstruction for accelerated MRI T Weiss, S Vedula, O Senouf, A Bronstein, O Michailovich, M Zibulevsky ICASSP 2020, 2019 | 33* | 2019 |
| Learning beamforming in ultrasound imaging S Vedula, O Senouf, G Zurakhov, A Bronstein, O Michailovich, ... MIDL 2019, 2018 | 29 | 2018 |
| High quality ultrasonic multi-line transmission through deep learning S Vedula, O Senouf, G Zurakhov, A Bronstein, M Zibulevsky, ... Machine Learning for Medical Image Reconstruction: First International …, 2018 | 23 | 2018 |
| 3D FLAT-Feasible Learned Acquisition Trajectories for Accelerated MRI J Alush-Aben, L Ackerman, T Weiss, S Vedula, O Senouf, A Bronstein MLMIR, MICCAI 2020, 2020 | 19* | 2020 |
| Spectral Geometric Matrix Completion A Boyarski, S Vedula, A Bronstein Mathematical and Scientific Machine Learning, 172-196, 2022 | 16* | 2022 |
| Mint: An accelerator for mining temporal motifs N Talati, H Ye, S Vedula, KY Chen, Y Chen, D Liu, Y Yuan, D Blaauw, ... 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO …, 2022 | 6 | 2022 |
| Fast Nonlinear Vector Quantile Regression AA Rosenberg, S Vedula, Y Romano, AM Bronstein International Conference on Learning Representations (ICLR), 2023 | 4 | 2023 |
| Joint optimization of system design and reconstruction in mimo radar imaging T Weiss, N Peretz, S Vedula, A Feuer, A Bronstein 2021 IEEE 31st International Workshop on Machine Learning for Signal …, 2021 | 4 | 2021 |
| Towards Learned Optimal q-Space Sampling in Diffusion MRI T Weiss, S Vedula, O Senouf, O Michailovich, A Bronstein Computational Diffusion MRI, 13-28, 2021 | 3 | 2021 |
| Demystifying graph sparsification algorithms in graph properties preservation Y Chen, H Ye, S Vedula, A Bronstein, R Dreslinski, T Mudge, N Talati Proceedings of the VLDB Endowment 17 (3), 427-440, 2023 | 1 | 2023 |
| GRACE: A Scalable Graph-Based Approach to Accelerating Recommendation Model Inference H Ye, S Vedula, Y Chen, Y Yang, A Bronstein, R Dreslinski, T Mudge, ... Proceedings of the 28th ACM International Conference on Architectural …, 2023 | 1 | 2023 |
| Systems and methods for ultrasonic imaging O Senouf, S Vedula, A Bronstein, M Zibulevsky, G Zurakhov, ... US Patent 11,158,052, 2021 | 1 | 2021 |
| Method and system for training a machine learning procedure to analyze a radar signal A Bronstein, T Weiss, N Peretz, S Vedula, A Feuer US Patent App. 18/376,465, 2024 | | 2024 |
| Everest: GPU-Accelerated System For Mining Temporal Motifs Y Yuan, H Ye, S Vedula, W Kaza, N Talati arXiv preprint arXiv:2310.02800, 2023 | | 2023 |
| Continuous Vector Quantile Regression S Vedula, I Tallini, AA Rosenberg, M Pegoraro, E Rodolà, Y Romano, ... ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023 | | 2023 |
| Vector Quantile Regression on Manifolds M Pegoraro, S Vedula, AA Rosenberg, I Tallini, E Rodolà, AM Bronstein arXiv preprint arXiv:2307.01037, 2023 | | 2023 |
Alex BronsteinDan Broida Academic Chair, Schmidt Chair of AI, CS@TechnionVerified email at technion.ac.il
