Alex M. Bronstein

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 64

Top Topics

Reinforcement Learning

Quantile Regression

Image Stabilization

Top Venues

SIAM J. Imaging Sci.

Proc. VLDB Endow.

Publications

Daniel Freedman, Eyal Rozenberg, Alex M. Bronstein
A Theoretical Framework for an Efficient Normalizing Flow-Based Solution to the Schrodinger Equation. CoRR (2024)
Marco Pegoraro, Sanketh Vedula, Aviv Rosenberg, Irene Tallini, Emanuele Rodolà, Alex M. Bronstein
Vector Quantile Regression on Manifolds. AISTATS (2024)
Gabriele Serussi, Tamir Shor, Tom Hirshberg, Chaim Baskin, Alex M. Bronstein
Active propulsion noise shaping for multi-rotor aircraft localization. CoRR (2024)
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)
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) (2023)
Dean Zadok, Oren Salzman, Alon Wolf, Alex M. Bronstein
Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation. ICRA (2023)
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 (2023)
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 (2023)
Tamir Shor, Tomer Weiss, Dor Noti, Alex M. Bronstein
Multi PILOT: Learned Feasible Multiple Acquisition Trajectories for Dynamic MRI. CoRR (2023)
Marco Pegoraro, Sanketh Vedula, Aviv A. Rosenberg, Irene Tallini, Emanuele Rodolà, Alex M. Bronstein
Vector Quantile Regression on Manifolds. CoRR (2023)
Barak Gahtan, Reuven Cohen, Alex M. Bronstein, Gil Kedar
Using Deep Reinforcement Learning for mmWave Real-Time Scheduling. NoF (2023)
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)
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) (2023)
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) (2023)
Dean Zadok, Oren Salzman, Alon Wolf, Alex M. Bronstein
Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation. CoRR (2022)
Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex M. Bronstein, Michael Elad
Threat Model-Agnostic Adversarial Defense using Diffusion Models. CoRR (2022)
Aviv A. Rosenberg, Sanketh Vedula, Yaniv Romano, Alex M. Bronstein
Fast Nonlinear Vector Quantile Regression. CoRR (2022)
Dan Navon, Alex M. Bronstein
Random Search Hyper-Parameter Tuning: Expected Improvement Estimation and the Corresponding Lower Bound. CoRR (2022)
Yaniv Nemcovsky, Matan Jacoby, Alex M. Bronstein, Chaim Baskin
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems. ACCV (7) (2022)
Barak Gahtan, Reuven Cohen, Alex M. Bronstein, Gil Kedar
Deep Reinforcement Learning for Scheduling and Power Allocation in a 5G Urban Mesh. CoRR (2022)
Gautam Pai, Alex M. Bronstein, Ronen Talmon, Ron Kimmel
Deep Isometric Maps. Image Vis. Comput. 123 (2022)
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)
Dan Navon, Alex M. Bronstein
Transformer Vs. MLP-Mixer Exponential Expressive Gap For NLP Problems. CoRR (2022)
Stefan Sommer, Alex M. Bronstein
Horizontal Flows and Manifold Stochastics in Geometric Deep Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44 (2) (2022)
Yaniv Nemcovsky, Matan Yaakoby, Alex M. Bronstein, Chaim Baskin
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems. CoRR (2022)
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 (2021)
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) (2021)
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)
Evgenii Zheltonozhskii, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Or Litany
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels. CoRR (2021)
Nir Diamant, Nitsan Sandor, Alex M. Bronstein
Delta-GAN-Encoder: Encoding Semantic Changes for Explicit Image Editing, using Few Synthetic Samples. CoRR (2021)
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)
Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson
Loss aware post-training quantization. Mach. Learn. 110 (11) (2021)
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 (2021)
Elad Amrani, Alex M. Bronstein
Self-Supervised Classification Network. CoRR (2021)
Eli Schwartz, Alex M. Bronstein, Raja Giryes
ISP Distillation. CoRR (2021)
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 (2021)
Tomer Weiss, Nissim Peretz, Sanketh Vedula, Arie Feuer, Alex M. Bronstein
Joint optimization of system design and reconstruction in MIMO radar imaging. CoRR (2021)
Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alex M. Bronstein, Davide Mottin, Panagiotis Karras
GRASP: Graph Alignment through Spectral Signatures. CoRR (2021)
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 (2021)
Omer Dahary, Matan Jacoby, Alex M. Bronstein
Digital Gimbal: End-to-End Deep Image Stabilization With Learnable Exposure Times. CVPR (2021)
Elad Amrani, Rami Ben-Ari, Daniel Rotman, Alex M. Bronstein
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning. AAAI (2021)
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 (2020)
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)
Omer Dahary, Matan Jacoby, Alex M. Bronstein
Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure Times. CoRR (2020)
Tomer Weiss, Sanketh Vedula, Ortal Senouf, Oleg V. Michailovich, Alex M. Bronstein
Towards learned optimal q-space sampling in diffusion MRI. CoRR (2020)
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)
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 (2020)
Or Litany, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronstein, Daniel Cremers
Non-Rigid Puzzles. CoRR (2020)
Keren Rotker, Dafna Ben-Bashat, Alex M. Bronstein
Overparameterized Models for Vector Fields. SIAM J. Imaging Sci. 13 (3) (2020)
Elad Amrani, Rami Ben-Ari, Inbar Shapira, Tal Hakim, Alex M. Bronstein
Self-Supervised Object Detection and Retrieval Using Unlabeled Videos. CVPR Workshops (2020)
Nir Diamant, Tal Mund, Ohad Menashe, Aviad Zabatani, Alex M. Bronstein
SimuGAN: Unsupervised forward modeling and optimal design of a LIDAR Camera. CoRR (2020)
Amir Livne, Ziv Aviv, Shahaf Grofit, Alex M. Bronstein, Ron Kimmel
Do We Need Depth in State-Of-The-Art Face Authentication? 3DV (2020)
Elad Amrani, Rami Ben-Ari, Daniel Rotman, Alex M. Bronstein
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning. CoRR (2020)
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)
Evgenii Zheltonozhskii, Chaim Baskin, Yaniv Nemcovsky, Brian Chmiel, Avi Mendelson, Alex M. Bronstein
Colored Noise Injection for Training Adversarially Robust Neural Networks. CoRR (2020)
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 (2020)
Evgenii Zheltonozhskii, Chaim Baskin, Alex M. Bronstein, Avi Mendelson
Self-Supervised Learning for Large-Scale Unsupervised Image Clustering. CoRR (2020)
Stefan Sommer, Alex M. Bronstein
Horizontal Flows and Manifold Stochastics in Geometric Deep Learning. CoRR (2019)
Eyal Rozenberg, Daniel Freedman, Alex M. Bronstein
Localization with Limited Annotation for Chest X-rays. ML4H@NeurIPS (2019)
Elad Amrani, Rami Ben-Ari, Tal Hakim, Alex M. Bronstein
Learning to Detect and Retrieve Objects From Unlabeled Videos. ICCV Workshops (2019)
Elad Amrani, Rami Ben-Ari, Tal Hakim, Alex M. Bronstein
Toward Self-Supervised Object Detection in Unlabeled Videos. CoRR (2019)
Amit Boyarski, Sanketh Vedula, Alex M. Bronstein
Deep geometric matrix completion: Are we doing it right? CoRR (2019)
Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein, Michael M. Bronstein, Justin Solomon
Functional Maps on Product Manifolds. SGP (Posters) (2018)
Xiao Bian, Hamid Krim, Alex M. Bronstein, Liyi Dai
Sparsity and Nullity: Paradigms for Analysis Dictionary Learning. SIAM J. Imaging Sci. 9 (3) (2016)
Xiao Bian, Hamid Krim, Alex M. Bronstein, Liyi Dai
Sparse null space basis pursuit and analysis dictionary learning for high-dimensional data analysis. ICASSP (2015)
Raid Saabni, Alex M. Bronstein
Fast Keyword Searching Using 'BoostMap' Based Embedding. ICFHR (2012)
Raid Saabni, Alex M. Bronstein
Fast Key-Word Searching via Embedding and Active-DTW. ICDAR (2011)