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ORCIDAlexander M. Bronstein
Alex M. Bronstein
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- affiliation: Technion - Israel Institute of Technology, Department of Computer Science
- affiliation: Tel Aviv University, School of Electrical Engineering
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2020 – today
- 2024
[c137]Gilad Rave, Daniel E. Fordham, Alex M. Bronstein, David H. Silver:
Enhancing Predictive Accuracy in Embryo Implantation: The Bonna Algorithm and its Clinical Implications. AIiH (2) 2024: 160-171- [c136]Marco Pegoraro, Sanketh Vedula, Aviv Rosenberg, Irene Tallini, Emanuele Rodolà, Alex M. Bronstein:
Vector Quantile Regression on Manifolds. AISTATS 2024: 1999-2007 - [i108]Gabriele Serussi, Tamir Shor, Tom Hirshberg, Chaim Baskin, Alex M. Bronstein:
Active propulsion noise shaping for multi-rotor aircraft localization. CoRR abs/2402.17289 (2024) - [i107]Tamir Shor, Chaim Baskin, Alexander M. Bronstein:
Leveraging Latents for Efficient Thermography Classification and Segmentation. CoRR abs/2404.06589 (2024) - [i106]Daniel Freedman, Eyal Rozenberg, Alex M. Bronstein:
A Theoretical Framework for an Efficient Normalizing Flow-Based Solution to the Schrodinger Equation. CoRR abs/2406.00047 (2024) - [i105]Sanketh Vedula, Valentino Maiorca, Lorenzo Basile, Francesco Locatello, Alexander M. Bronstein:
Scalable unsupervised alignment of general metric and non-metric structures. CoRR abs/2406.13507 (2024) - 2023
- [j67]Yaniv Nemcovsky, Evgenii Zheltonozhskii
, Chaim Baskin, Brian Chmiel, Alex M. Bronstein, Avi Mendelson:
Adversarial robustness via noise injection in smoothed models. Appl. Intell. 53(8): 9483-9498 (2023) - [j66]Tomer Weiss, Eduardo Mayo Yanes, Sabyasachi Chakraborty, Luca Cosmo, Alex M. Bronstein, Renana Gershoni-Poranne:
Guided diffusion for inverse molecular design. Nat. Comput. Sci. 3(10): 873-882 (2023) - [j65]Yuhan Chen, Haojie Ye, Sanketh Vedula, Alex M. Bronstein, Ronald G. Dreslinski, Trevor N. Mudge, Nishil Talati:
Demystifying Graph Sparsification Algorithms in Graph Properties Preservation. Proc. VLDB Endow. 17(3): 427-440 (2023) - [j64]Judith Hermanns, Konstantinos Skitsas, Anton Tsitsulin, Marina Munkhoeva, Alexander Frederiksen Kyster, Simon Nielsen, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Scalable Graph Alignment by Spectral Corresponding Functions. ACM Trans. Knowl. Discov. Data 17(4): 50:1-50:26 (2023) - [c135]Haojie Ye, Sanketh Vedula, Yuhan Chen, Yichen Yang, Alex M. Bronstein, Ronald G. Dreslinski, Trevor N. Mudge, Nishil Talati:
GRACE: A Scalable Graph-Based Approach to Accelerating Recommendation Model Inference. ASPLOS (3) 2023: 282-301 - [c134]Aviv A. Rosenberg, Sanketh Vedula, Yaniv Romano, Alexander M. Bronstein:
Fast Nonlinear Vector Quantile Regression. ICLR 2023 - [c133]Dean Zadok, Oren Salzman, Alon Wolf, Alex M. Bronstein:
Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation. ICRA 2023: 12645-12651 - [c132]Ama Bembua Bainson, Judith Hermanns, Petros Petsinis, Niklas Aavad, Casper Dam Larsen, Tiarnan Swayne, Amit Boyarski, Davide Mottin, Alex M. Bronstein, Panagiotis Karras:
Spectral Subgraph Localization. LoG 2023: 7 - [c131]Tamir Shor, Tomer Weiss, Dor Noti, Alexander M. Bronstein:
Multi PILOT: Feasible Learned Multiple Acquisition Trajectories For Dynamic MRI. MIDL 2023: 1033-1050 - [c130]Barak Gahtan, Reuven Cohen, Alex M. Bronstein, Gil Kedar:
Using Deep Reinforcement Learning for mmWave Real-Time Scheduling. NoF 2023: 71-79 - [i104]Tamir Shor, Tomer Weiss, Dor Noti, Alex M. Bronstein:
Multi PILOT: Learned Feasible Multiple Acquisition Trajectories for Dynamic MRI. CoRR abs/2303.07150 (2023) - [i103]Tsachi Blau, Roy Ganz, Chaim Baskin, Michael Elad, Alexander M. Bronstein:
Classifier Robustness Enhancement Via Test-Time Transformation. CoRR abs/2303.15409 (2023) - [i102]Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Joshua Foley-Comer, Sivan Trajtenberg-Mills, Sarika Mishra, Shashi Prabhakar, Ravindra Pratap Singh, Daniel Freedman, Alex M. Bronstein, Ady Arie:
Designing Nonlinear Photonic Crystals for High-Dimensional Quantum State Engineering. CoRR abs/2304.06810 (2023) - [i101]Marco Pegoraro, Sanketh Vedula, Aviv A. Rosenberg, Irene Tallini, Emanuele Rodolà, Alex M. Bronstein:
Vector Quantile Regression on Manifolds. CoRR abs/2307.01037 (2023) - [i100]Yuhan Chen, Haojie Ye, Sanketh Vedula, Alex M. Bronstein, Ronald G. Dreslinski, Trevor N. Mudge, Nishil Talati:
Demystifying Graph Sparsification Algorithms in Graph Properties Preservation. CoRR abs/2311.12314 (2023) - 2022
- [j63]Peipei Kang, Zehang Lin, Zhenguo Yang, Xiaozhao Fang, Alexander M. Bronstein, Qing Li, Wenyin Liu:
Intra-class low-rank regularization for supervised and semi-supervised cross-modal retrieval. Appl. Intell. 52(1): 33-54 (2022) - [j62]Gautam Pai, Alex M. Bronstein, Ronen Talmon, Ron Kimmel:
Deep Isometric Maps. Image Vis. Comput. 123: 104461 (2022) - [j61]Peipei Kang, Zehang Lin, Zhenguo Yang, Alexander M. Bronstein, Qing Li, Wenyin Liu:
Deep fused two-step cross-modal hashing with multiple semantic supervision. Multim. Tools Appl. 81(11): 15653-15670 (2022) - [j60]Stefan Sommer, Alex M. Bronstein:
Horizontal Flows and Manifold Stochastics in Geometric Deep Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 811-822 (2022) - [j59]Eli Schwartz, Leonid Karlinsky, Rogério Feris, Raja Giryes, Alexander M. Bronstein:
Baby steps towards few-shot learning with multiple semantics. Pattern Recognit. Lett. 160: 142-147 (2022) - [c129]Yaniv Nemcovsky, Matan Jacoby, Alex M. Bronstein, Chaim Baskin:
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems. ACCV (7) 2022: 518-534 - [c128]Elad Amrani, Leonid Karlinsky, Alexander M. Bronstein:
Self-Supervised Classification Network. ECCV (31) 2022: 116-132 - [c127]Nishil Talati, Haojie Ye, Sanketh Vedula, Kuan-Yu Chen, Yuhan Chen, Daniel Liu, Yichao Yuan, David T. Blaauw, Alex M. Bronstein, Trevor N. Mudge, Ronald G. Dreslinski:
Mint: An Accelerator For Mining Temporal Motifs. MICRO 2022: 1270-1287 - [c126]Evgenii Zheltonozhskii, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Or Litany:
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels. WACV 2022: 387-397 - [i99]Dean Zadok, Oren Salzman, Alon Wolf, Alex M. Bronstein:
Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation. CoRR abs/2202.05204 (2022) - [i98]Aviv A. Rosenberg, Sanketh Vedula, Yaniv Romano, Alex M. Bronstein:
Fast Nonlinear Vector Quantile Regression. CoRR abs/2205.14977 (2022) - [i97]Yaniv Nemcovsky, Matan Yaakoby, Alex M. Bronstein, Chaim Baskin:
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems. CoRR abs/2207.05729 (2022) - [i96]Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex M. Bronstein, Michael Elad:
Threat Model-Agnostic Adversarial Defense using Diffusion Models. CoRR abs/2207.08089 (2022) - [i95]Dan Navon, Alex M. Bronstein:
Random Search Hyper-Parameter Tuning: Expected Improvement Estimation and the Corresponding Lower Bound. CoRR abs/2208.08170 (2022) - [i94]Dan Navon, Alex M. Bronstein:
Transformer Vs. MLP-Mixer Exponential Expressive Gap For NLP Problems. CoRR abs/2208.08191 (2022) - [i93]Barak Gahtan, Reuven Cohen, Alex M. Bronstein, Gil Kedar:
Deep Reinforcement Learning for Scheduling and Power Allocation in a 5G Urban Mesh. CoRR abs/2210.01423 (2022) - [i92]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
Spectral Graph Complexity. CoRR abs/2211.01434 (2022) - 2021
- [j58]Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson:
CAT: Compression-Aware Training for bandwidth reduction. J. Mach. Learn. Res. 22: 269:1-269:20 (2021) - [j57]Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson:
Loss aware post-training quantization. Mach. Learn. 110(11): 3245-3262 (2021) - [j56]Sivan Doveh, Eli Schwartz, Chao Xue, Rogério Feris, Alexander M. Bronstein, Raja Giryes, Leonid Karlinsky:
MetAdapt: Meta-learned task-adaptive architecture for few-shot classification. Pattern Recognit. Lett. 149: 130-136 (2021) - [c125]Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Feris, Alex M. Bronstein, Raja Giryes:
StarNet: towards Weakly Supervised Few-Shot Object Detection. AAAI 2021: 1743-1753 - [c124]Elad Amrani, Rami Ben-Ari, Daniel Rotman, Alex M. Bronstein:
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning. AAAI 2021: 6644-6652 - [c123]Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Graph Alignment Through Spectral Signatures. APWeb/WAIM (1) 2021: 44-52 - [c122]Omer Dahary, Matan Jacoby, Alex M. Bronstein:
Digital Gimbal: End-to-End Deep Image Stabilization With Learnable Exposure Times. CVPR 2021: 11936-11945 - [c121]Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky:
Detector-Free Weakly Supervised Grounding by Separation. ICCV 2021: 1781-1792 - [c120]Tomer Weiss, Nissim Peretz, Sanketh Vedula, Arie Feuer, Alexander M. Bronstein:
Joint Optimization of System Design and Reconstruction in MIMO Radar Imaging. MLSP 2021: 1-6 - [c119]Amit Boyarski, Sanketh Vedula, Alexander M. Bronstein:
Spectral Geometric Matrix Completion. MSML 2021: 172-196 - [i91]Eli Schwartz, Alex M. Bronstein, Raja Giryes:
ISP Distillation. CoRR abs/2101.10203 (2021) - [i90]Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Sivan Trajtenberg-Mills, Daniel Freedman, Alex M. Bronstein, Ady Arie:
Inverse Design of Quantum Holograms in Three-Dimensional Nonlinear Photonic Crystals. CoRR abs/2102.10344 (2021) - [i89]Elad Amrani, Alex M. Bronstein:
Self-Supervised Classification Network. CoRR abs/2103.10994 (2021) - [i88]Evgenii Zheltonozhskii, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Or Litany:
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels. CoRR abs/2103.13646 (2021) - [i87]Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky:
Detector-Free Weakly Supervised Grounding by Separation. CoRR abs/2104.09829 (2021) - [i86]Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alex M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Graph Alignment through Spectral Signatures. CoRR abs/2106.05729 (2021) - [i85]Tomer Weiss, Nissim Peretz, Sanketh Vedula, Arie Feuer, Alex M. Bronstein:
Joint optimization of system design and reconstruction in MIMO radar imaging. CoRR abs/2110.03218 (2021) - [i84]Nir Diamant, Nitsan Sandor, Alex M. Bronstein:
Delta-GAN-Encoder: Encoding Semantic Changes for Explicit Image Editing, using Few Synthetic Samples. CoRR abs/2111.08419 (2021) - [i83]Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Joshua Foley-Comer, Sivan Trajtenberg-Mills, Daniel Freedman, Alex M. Bronstein, Ady Arie:
SPDCinv: Inverse Quantum-Optical Design of High-Dimensional Qudits. CoRR abs/2112.05934 (2021) - 2020
- [j55]Giorgio Mariani, Luca Cosmo, Alexander M. Bronstein, Emanuele Rodolà:
Generating Adversarial Surfaces via Band-Limited Perturbations. Comput. Graph. Forum 39(5): 253-264 (2020) - [j54]Aviad Zabatani, Vitaly Surazhsky, Erez Sperling, Sagi Ben-Moshe, Ohad Menashe, David H. Silver, Zachi Karni, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Intel® RealSense™ SR300 Coded Light Depth Camera. IEEE Trans. Pattern Anal. Mach. Intell. 42(10): 2333-2345 (2020) - [j53]Keren Rotker, Dafna Ben-Bashat, Alex M. Bronstein:
Overparameterized Models for Vector Fields. SIAM J. Imaging Sci. 13(3): 1386-1414 (2020) - [j52]Raja Giryes, Guillermo Sapiro, Alex M. Bronstein:
Corrections to "Deep Neural Networks With Random Gaussian Weights: A Universal Classification Strategy?". IEEE Trans. Signal Process. 68: 529-531 (2020) - [j51]Yoni Choukroun, Alon Shtern, Alexander M. Bronstein, Ron Kimmel:
Hamiltonian Operator for Spectral Shape Analysis. IEEE Trans. Vis. Comput. Graph. 26(2): 1320-1331 (2020) - [c118]Amir Livne, Ziv Aviv, Shahaf Grofit, Alex M. Bronstein, Ron Kimmel:
Do We Need Depth in State-Of-The-Art Face Authentication? 3DV 2020: 889-897 - [c117]Elad Amrani, Rami Ben-Ari, Inbar Shapira, Tal Hakim, Alex M. Bronstein:
Self-Supervised Object Detection and Retrieval Using Unlabeled Videos. CVPR Workshops 2020: 4100-4108 - [c116]Tomer Weiss, Sanketh Vedula, Ortal Senouf, Oleg V. Michailovich, Michael Zibulevsky, Alexander M. Bronstein:
Joint Learning of Cartesian under Sampling Andre Construction for Accelerated MRI. ICASSP 2020: 8653-8657 - [c115]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller:
The Shape of Data: Intrinsic Distance for Data Distributions. ICLR 2020 - [c114]Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Yevgeny Yermolin, Alex Karbachevsky, Alex M. Bronstein, Avi Mendelson:
Feature Map Transform Coding for Energy-Efficient CNN Inference. IJCNN 2020: 1-9 - [c113]Jonathan Alush-Aben, Linor Ackerman-Schraier, Tomer Weiss, Sanketh Vedula, Ortal Senouf, Alex M. Bronstein:
3D FLAT: Feasible Learned Acquisition Trajectories for Accelerated MRI. MLMIR@MICCAI 2020: 3-16 - [c112]Moran Shkolnik, Brian Chmiel, Ron Banner, Gil Shomron, Yury Nahshan, Alex M. Bronstein, Uri C. Weiser:
Robust Quantization: One Model to Rule Them All. NeurIPS 2020 - [i82]Moran Shkolnik, Brian Chmiel, Ron Banner, Gil Shomron, Yury Nahshan, Alexander M. Bronstein, Uri C. Weiser:
Robust Quantization: One Model to Rule Them All. CoRR abs/2002.07686 (2020) - [i81]Evgenii Zheltonozhskii, Chaim Baskin, Yaniv Nemcovsky, Brian Chmiel, Avi Mendelson, Alex M. Bronstein:
Colored Noise Injection for Training Adversarially Robust Neural Networks. CoRR abs/2003.02188 (2020) - [i80]Elad Amrani, Rami Ben-Ari, Daniel Rotman, Alex M. Bronstein:
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning. CoRR abs/2003.03186 (2020) - [i79]Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Schmidt Feris, Alexander M. Bronstein, Raja Giryes:
StarNet: towards weakly supervised few-shot detection and explainable few-shot classification. CoRR abs/2003.06798 (2020) - [i78]David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, Long Lai, Bo Li, Chunyuan Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Li Sun, Gary K. L. Tam, Atsushi Tatsuma, Jianbo Ye:
Shape retrieval of non-rigid 3d human models. CoRR abs/2003.08763 (2020) - [i77]Amir Livne, Alexander M. Bronstein, Ron Kimmel, Ziv Aviv, Shahaf Grofit:
Do We Need Depth in State-Of-The-Art Face Authentication? CoRR abs/2003.10895 (2020) - [i76]Alex Karbachevsky, Chaim Baskin, Evgenii Zheltonozhskii, Yevgeny Yermolin, Freddy Gabbay, Alex M. Bronstein, Avi Mendelson:
HCM: Hardware-Aware Complexity Metric for Neural Network Architectures. CoRR abs/2004.08906 (2020) - [i75]David H. Silver, Martin Feder, Yael Gold-Zamir, Avital L. Polsky, Shahar Rosentraub, Efrat Shachor, Adi Weinberger, Pavlo Mazur, Valery D. Zukin, Alex M. Bronstein:
Data-Driven Prediction of Embryo Implantation Probability Using IVF Time-lapse Imaging. CoRR abs/2006.01035 (2020) - [i74]Jonathan Alush-Aben, Linor Ackerman-Schraier, Tomer Weiss, Sanketh Vedula, Ortal Senouf, Alexander M. Bronstein:
3D FLAT: Feasible Learned Acquisition Trajectories for Accelerated MRI. CoRR abs/2008.04808 (2020) - [i73]Evgenii Zheltonozhskii, Chaim Baskin, Alex M. Bronstein, Avi Mendelson:
Self-Supervised Learning for Large-Scale Unsupervised Image Clustering. CoRR abs/2008.10312 (2020) - [i72]Tomer Weiss, Sanketh Vedula, Ortal Senouf, Oleg V. Michailovich, Alex M. Bronstein:
Towards learned optimal q-space sampling in diffusion MRI. CoRR abs/2009.03008 (2020) - [i71]Or Litany, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronstein, Daniel Cremers:
Non-Rigid Puzzles. CoRR abs/2011.13076 (2020) - [i70]Omer Dahary, Matan Jacoby, Alex M. Bronstein:
Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure Times. CoRR abs/2012.04515 (2020) - [i69]Nir Diamant, Tal Mund, Ohad Menashe, Aviad Zabatani, Alex M. Bronstein:
SimuGAN: Unsupervised forward modeling and optimal design of a LIDAR Camera. CoRR abs/2012.08951 (2020)
2010 – 2019
- 2019
- [j50]Emanuele Rodolà, Zorah Lähner, Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps Representation On Product Manifolds. Comput. Graph. Forum 38(1): 678-689 (2019) - [j49]Eli Schwartz, Raja Giryes, Alexander M. Bronstein:
DeepISP: Toward Learning an End-to-End Image Processing Pipeline. IEEE Trans. Image Process. 28(2): 912-923 (2019) - [j48]Chaim Baskin, Natan Liss, Eli Schwartz, Evgenii Zheltonozhskii, Raja Giryes, Alex M. Bronstein, Avi Mendelson:
UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks. ACM Trans. Comput. Syst. 37(1-4): 4:1-4:15 (2019) - [c111]Arianna Rampini, Irene Tallini, Maks Ovsjanikov, Alexander M. Bronstein, Emanuele Rodolà:
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment. 3DV 2019: 37-46 - [c110]Roberto M. Dyke, C. Stride, Yu-Kun Lai, Paul L. Rosin, Mathieu Aubry, Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers, Matthew Fisher, Thibault Groueix, Daoliang Guo, Vladimir G. Kim, Ron Kimmel, Zorah Lähner, Kun Li, Or Litany, Tal Remez, Emanuele Rodolà, Bryan C. Russell, Yusuf Sahillioglu, Ron Slossberg, Gary K. L. Tam, Matthias Vestner, Z. Wu, Jingyu Yang:
Shape Correspondence with Isometric and Non-Isometric Deformations. 3DOR@Eurographics 2019: 111-119 - [c109]Oshri Halimi, Or Litany, Emanuele Rodolà, Alexander M. Bronstein, Ron Kimmel:
Unsupervised Learning of Dense Shape Correspondence. CVPR 2019: 4370-4379 - [c108]Leonid Karlinsky, Joseph Shtok, Sivan Harary, Eli Schwartz, Amit Aides, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein:
RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection. CVPR 2019: 5197-5206 - [c107]Amit Alfassy, Leonid Karlinsky, Amit Aides, Joseph Shtok, Sivan Harary, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein:
LaSO: Label-Set Operations Networks for Multi-Label Few-Shot Learning. CVPR 2019: 6548-6557 - [c106]Elad Amrani, Rami Ben-Ari, Tal Hakim, Alex M. Bronstein:
Learning to Detect and Retrieve Objects From Unlabeled Videos. ICCV Workshops 2019: 3713-3717 - [c105]Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alexander M. Bronstein:
Beholder-Gan: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level. ICIP 2019: 739-743 - [c104]Ortal Senouf, Sanketh Vedula, Tomer Weiss, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky:
Self-supervised Learning of Inverse Problem Solvers in Medical Imaging. DART/MIL3ID@MICCAI 2019: 111-119 - [c103]Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky:
Learning beamforming in ultrasound imaging. MIDL 2019: 493-511 - [c102]Eyal Rozenberg, Daniel Freedman, Alex M. Bronstein:
Localization with Limited Annotation for Chest X-rays. ML4H@NeurIPS 2019: 52-65 - [c101]Gautam Pai, Ronen Talmon, Alexander M. Bronstein, Ron Kimmel:
DIMAL: Deep Isometric Manifold Learning Using Sparse Geodesic Sampling. WACV 2019: 819-828 - [c100]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
Spectral Graph Complexity. WWW (Companion Volume) 2019: 308-309 - [i68]Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alexander M. Bronstein:
Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level. CoRR abs/1902.02593 (2019) - [i67]Amit Alfassy, Leonid Karlinsky, Amit Aides, Joseph Shtok, Sivan Harary, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein:
LaSO: Label-Set Operations networks for multi-label few-shot learning. CoRR abs/1902.09811 (2019) - [i66]Yochai Zur, Chaim Baskin, Evgenii Zheltonozhskii, Brian Chmiel, Itay Evron, Alexander M. Bronstein, Avi Mendelson:
Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks. CoRR abs/1904.09872 (2019) - [i65]Tomer Weiss, Sanketh Vedula, Ortal Senouf, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky:
Learning Fast Magnetic Resonance Imaging. CoRR abs/1905.09324 (2019) - [i64]Ortal Senouf, Sanketh Vedula, Tomer Weiss, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky:
Self-supervised learning of inverse problem solvers in medical imaging. CoRR abs/1905.09325 (2019) - [i63]Brian Chmiel, Chaim Baskin, Ron Banner, Evgenii Zheltonozhskii, Yevgeny Yermolin, Alex Karbachevsky, Alexander M. Bronstein, Avi Mendelson:
Feature Map Transform Coding for Energy-Efficient CNN Inference. CoRR abs/1905.10830 (2019) - [i62]Elad Amrani, Rami Ben-Ari, Tal Hakim, Alex M. Bronstein:
Toward Self-Supervised Object Detection in Unlabeled Videos. CoRR abs/1905.11137 (2019) - [i61]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller:
Intrinsic Multi-scale Evaluation of Generative Models. CoRR abs/1905.11141 (2019) - [i60]Eli Schwartz, Leonid Karlinsky, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein:
Baby steps towards few-shot learning with multiple semantics. CoRR abs/1906.01905 (2019) - [i59]Arianna Rampini, Irene Tallini, Maks Ovsjanikov, Alexander M. Bronstein, Emanuele Rodolà:
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment. CoRR abs/1906.06226 (2019) - [i58]Tomer Weiss, Ortal Senouf, Sanketh Vedula, Oleg V. Michailovich, Michael Zibulevsky, Alexander M. Bronstein:
PILOT: Physics-Informed Learned Optimal Trajectories for Accelerated MRI. CoRR abs/1909.05773 (2019) - [i57]Stefan Sommer, Alex M. Bronstein:
Horizontal Flows and Manifold Stochastics in Geometric Deep Learning. CoRR abs/1909.06397 (2019) - [i56]Eyal Rozenberg, Daniel Freedman, Alexander M. Bronstein:
Localization with Limited Annotation. CoRR abs/1909.08842 (2019) - [i55]Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alexander M. Bronstein, Avi Mendelson:
CAT: Compression-Aware Training for bandwidth reduction. CoRR abs/1909.11481 (2019) - [i54]Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alexander M. Bronstein, Avi Mendelson:
Loss Aware Post-training Quantization. CoRR abs/1911.07190 (2019) - [i53]