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Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels


Mar 25, 2021
Evgenii Zheltonozhskii, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Or Litany


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Inverse Design of Quantum Holograms in Three-Dimensional Nonlinear Photonic Crystals


Feb 20, 2021
Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Sivan Trajtenberg-Mills, Daniel Freedman, Alex M. Bronstein, Ady Arie

* A supporting code will be published shortly 

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SimuGAN: Unsupervised forward modeling and optimal design of a LIDAR Camera


Dec 16, 2020
Nir Diamant, Tal Mund, Ohad Menashe, Aviad Zabatani, Alex M. Bronstein


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Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure Times


Dec 08, 2020
Omer Dahary, Matan Jacoby, Alex M. Bronstein


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Self-Supervised Learning for Large-Scale Unsupervised Image Clustering


Aug 24, 2020
Evgenii Zheltonozhskii, Chaim Baskin, Alex M. Bronstein, Avi Mendelson


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Data-Driven Prediction of Embryo Implantation Probability Using IVF Time-lapse Imaging


Jun 02, 2020
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


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HCM: Hardware-Aware Complexity Metric for Neural Network Architectures


Apr 26, 2020
Alex Karbachevsky, Chaim Baskin, Evgenii Zheltonozhskii, Yevgeny Yermolin, Freddy Gabbay, Alex M. Bronstein, Avi Mendelson


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Colored Noise Injection for Training Adversarially Robust Neural Networks


Mar 20, 2020
Evgenii Zheltonozhskii, Chaim Baskin, Yaniv Nemcovsky, Brian Chmiel, Avi Mendelson, Alex M. Bronstein


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Smoothed Inference for Adversarially-Trained Models


Nov 17, 2019
Yaniv Nemcovsky, Evgenii Zheltonozhskii, Chaim Baskin, Brian Chmiel, Alex M. Bronstein, Avi Mendelson


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Loss Aware Post-training Quantization


Nov 17, 2019
Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson


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CAT: Compression-Aware Training for bandwidth reduction


Sep 25, 2019
Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson


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Baby steps towards few-shot learning with multiple semantics


Jun 05, 2019
Eli Schwartz, Leonid Karlinsky, Rogerio Feris, Raja Giryes, Alex M. Bronstein


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Feature Map Transform Coding for Energy-Efficient CNN Inference


May 26, 2019
Brian Chmiel, Chaim Baskin, Ron Banner, Evgenii Zheltonozhskii, Yevgeny Yermolin, Alex Karbachevsky, Alex M. Bronstein, Avi Mendelson


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Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks


Apr 29, 2019
Yochai Zur, Chaim Baskin, Evgenii Zheltonozhskii, Brian Chmiel, Itay Evron, Alex M. Bronstein, Avi Mendelson


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LaSO: Label-Set Operations networks for multi-label few-shot learning


Feb 26, 2019
Amit Alfassy, Leonid Karlinsky, Amit Aides, Joseph Shtok, Sivan Harary, Rogerio Feris, Raja Giryes, Alex M. Bronstein


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Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level


Feb 25, 2019
Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alex M. Bronstein


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Efficient non-uniform quantizer for quantized neural network targeting reconfigurable hardware


Nov 27, 2018
Natan Liss, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Raja Giryes

* In submission 

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UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks


Oct 02, 2018
Chaim Baskin, Eli Schwartz, Evgenii Zheltonozhskii, Natan Liss, Raja Giryes, Alex M. Bronstein, Avi Mendelson


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High frame-rate cardiac ultrasound imaging with deep learning


Aug 23, 2018
Ortal Senouf, Sanketh Vedula, Grigoriy Zurakhov, Alex M. Bronstein, Michael Zibulevsky, Oleg Michailovich, Dan Adam, David Blondheim

* To appear in the Proceedings of MICCAI, 2018 

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High quality ultrasonic multi-line transmission through deep learning


Aug 23, 2018
Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov, Alex M. Bronstein, Michael Zibulevsky, Oleg Michailovich, Dan Adam, Diana Gaitini

* To appear in Proceedings of MLMIR workshop, MICCAI 2018 

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Class-Aware Fully-Convolutional Gaussian and Poisson Denoising


Aug 20, 2018
Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein


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RepMet: Representative-based metric learning for classification and one-shot object detection


Jun 15, 2018
Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Sharathchandra Pankanti, Rogerio Feris, Abhishek Kumar, Raja Giryes, Alex M. Bronstein


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Delta-encoder: an effective sample synthesis method for few-shot object recognition


Jun 12, 2018
Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Rogerio Feris, Abhishek Kumar, Raja Giryes, Alex M. Bronstein


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Tradeoffs between Convergence Speed and Reconstruction Accuracy in Inverse Problems


Feb 15, 2018
Raja Giryes, Yonina C. Eldar, Alex M. Bronstein, Guillermo Sapiro

* To appear in IEEE Transactions on Signal Processing 

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DeepISP: Learning End-to-End Image Processing Pipeline


Jan 20, 2018
Eli Schwartz, Raja Giryes, Alex M. Bronstein


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Towards CT-quality Ultrasound Imaging using Deep Learning


Oct 17, 2017
Sanketh Vedula, Ortal Senouf, Alex M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky


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