Nadav Cohen

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Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design pdf

Amnon Shashua, Nadav Cohen, David Yakira, 2017, ICLR.

On the Expressive Power of Deep Learning: A Tensor Analysis

Nadav Cohen, Or Sharir, Amnon Shashua, 2015, COLT 2016.

On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization pdf

Sanjeev Arora, Nadav Cohen, Elad Hazan, 2018, ICML.

Convolutional Rectifier Networks as Generalized Tensor Decompositions pdf

Amnon Shashua, Nadav Cohen, A. Shashua, 2016, ICML.

BeamsNet: A data-driven Approach Enhancing Doppler Velocity Log Measurements for Autonomous Underwater Vehicle Navigation

Nadav Cohen, I. Klein, 2022, Eng. Appl. Artif. Intell..

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks

Nadav Cohen, Noam Razin, Asaf Maman, 2022, ICML.

Deep Linear Networks for Matrix Completion -- An Infinite Depth Limit

Nadav Cohen, Govind Menon, Zsolt Veraszto, 2022, 2210.12497.

LiBeamsNet: AUV Velocity Vector Estimation in Situations of Limited DVL Beam Measurements

Nadav Cohen, I. Klein, 2022, OCEANS 2022, Hampton Roads.

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network

A. Globerson, R. Giryes, Nadav Cohen, 2022, ArXiv.

On the Ability of Graph Neural Networks to Model Interactions Between Vertices

Nadav Cohen, Noam Razin, Tom Verbin, 2022, 2211.16494.

On the Ability of Graph Neural Networks to Model Interactions Between Vertices

Nadav Cohen, Noam Razin, Tom Verbin, 2022, ArXiv.

Implicit Regularization in Deep Matrix Factorization

Sanjeev Arora, Wei Hu, Nadav Cohen, 2019, NeurIPS.

Quantum Entanglement in Deep Learning Architectures.

Amnon Shashua, Nadav Cohen, Or Sharir, 2018, Physical review letters.

"Zero-Shot" Super-Resolution Using Deep Internal Learning

Michal Irani, Nadav Cohen, Assaf Shocher, 2017, CVPR.

Continuous vs. Discrete Optimization of Deep Neural Networks pdf

Nadav Cohen, Omer Elkabetz, Nadav Cohen, 2021, NeurIPS.

Implicit Regularization in Deep Learning May Not Be Explainable by Norms pdf

Nadav Cohen, Noam Razin, Nadav Cohen, 2020, NeurIPS.

Inductive Bias of Deep Convolutional Networks through Pooling Geometry pdf

Amnon Shashua, Nadav Cohen, A. Shashua, 2016, ICLR.

Semantic Segmentation in Art Paintings

Ariel Shamir, Nadav Cohen, Yael Newman, 2022, Comput. Graph. Forum.

A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks pdf

Wei Hu, Sanjeev Arora, Noah Golowich, 2018, ICLR.

On the Ability of Graph Neural Networks to Model Interactions Between Vertices

Nadav Cohen, Noam Razin, Tom Verbin, 2022, ArXiv.

What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement

Nadav Cohen, Yotam Alexander, Noam Razin, 2023, ArXiv.

Implicit Regularization in Tensor Factorization

Nadav Cohen, Noam Razin, Asaf Maman, 2021, ICML.

Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions pdf

Ronen Tamari, Amnon Shashua, Nadav Cohen, 2017, ArXiv.

Tensorial Mixture Models pdf

Ronen Tamari, Amnon Shashua, Nadav Cohen, 2017, ArXiv.

Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions pdf

Ronen Tamari, Amnon Shashua, Nadav Cohen, 2017, ICLR.

SimNets: A Generalization of Convolutional Networks pdf

Amnon Shashua, Nadav Cohen, A. Shashua, 2014, ArXiv.

Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions

Nadav Cohen, I. Klein, 2023, ArXiv.

On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization

Sanjeev Arora, Elad Hazan, Nadav Cohen, 2018, ICML.

On the Implicit Bias of Gradient Descent for Temporal Extrapolation

Avichai Ben David, A. Globerson, Nadav Cohen, 2022, AISTATS.

Deep Linear Networks for Matrix Completion - An Infinite Depth Limit

Nadav Cohen, Govind Menon, Zsolt Veraszto, 2022, SIAM J. Appl. Dyn. Syst..

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network

A. Globerson, R. Giryes, Nadav Cohen, 2022, International Conference on Learning Representations.

Deep neural network classification in the compressively sensed spectral image domain

Adrian Stern, Nadav Cohen, Yaniv Oiknine, 2021, J. Electronic Imaging.

On the Expressive Power of Deep Learning: A Tensor Analysis

A. Shashua, Nadav Cohen, Or Sharir, 2015, COLT.

Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks.

Nadav Cohen, Or Sharir, Amnon Shashua, 2018 .

On the Expressive Power of Deep Learning: A Tensor Analysis

A. Shashua, Nadav Cohen, Or Sharir, 2015, COLT.

What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement

Nadav Cohen, Yotam Alexander, Noam Razin, 2023, NeurIPS.

Notes on Hierarchical Splines, DCLNs and i-theory

Tomaso Poggio, Lorenzo Rosasco, Amnon Shashua, 2015 .

Zero-Shot Super-Resolution Using Deep Internal Learning

M. Irani, Nadav Cohen, Assaf Shocher, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks

A. Shashua, Yoav Levine, Nadav Cohen, 2018, ArXiv.

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets

A. Globerson, R. Giryes, Nadav Cohen, 2022, ICLR.

Tractable Generative Convolutional Arithmetic Circuits

Ronen Tamari, Amnon Shashua, Nadav Cohen, 2016, 1610.04167.

Continuous vs. Discrete Optimization of Deep Neural Networks

Nadav Cohen, Omer Elkabetz, 2021, NeurIPS.

Deep Learning and Quantum Physics : A Fundamental Bridge

Nadav Cohen, Amnon Shashua, David Yakira, 2017 .