Nadav Cohen

According to our database, Nadav Cohen authored at least 44 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States.

Noam Razin, Yotam Alexander, Edo Cohen-Karlik, Raja Giryes, Amir Globerson, Nadav Cohen

CoRR, 2024

Data-Driven Strategies for Coping with Incomplete DVL Measurements.

Nadav Cohen, Itzik Klein

CoRR, 2024

A-KIT: Adaptive Kalman-Informed Transformer.

Nadav Cohen, Itzik Klein

CoRR, 2024

2023

Deep Linear Networks for Matrix Completion - an Infinite Depth Limit.

Nadav Cohen, Govind Menon, Zsolt Veraszto

SIAM J. Appl. Dyn. Syst., December, 2023

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

Nadav Cohen, Itzik Klein

CoRR, 2023

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

Noam Razin, Tom Verbin, Nadav Cohen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Yotam Alexander, Nimrod De La Vega, Noam Razin, Nadav Cohen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets.

Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen, Amir Globerson

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

BeamsNet: A data-driven approach enhancing Doppler velocity log measurements for autonomous underwater vehicle navigation.

Nadav Cohen, Itzik Klein

Eng. Appl. Artif. Intell., 2022

Set-Transformer BeamsNet for AUV Velocity Forecasting in Complete DVL Outage Scenarios.

Nadav Cohen, Zeev Yampolsky, Itzik Klein

CoRR, 2022

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network.

Edo Cohen-Karlik, Itamar Menuhin-Gruman, Nadav Cohen, Raja Giryes, Amir Globerson

CoRR, 2022

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

Nadav Cohen, Itzik Klein

CoRR, 2022

Semantic Segmentation in Art Paintings.

Nadav Cohen, Yael Newman, Ariel Shamir

Comput. Graph. Forum, 2022

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks.

Noam Razin, Asaf Maman, Nadav Cohen

Proceedings of the International Conference on Machine Learning, 2022

On the Implicit Bias of Gradient Descent for Temporal Extrapolation.

Edo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Deep neural network classification in the compressively sensed spectral image domain.

Nadav Cohen, Shauli Shmilovich, Yaniv Oiknine, Adrian Stern

J. Electronic Imaging, 2021

Continuous vs. Discrete Optimization of Deep Neural Networks.

Omer Elkabetz, Nadav Cohen

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Implicit Regularization in Tensor Factorization.

Noam Razin, Asaf Maman, Nadav Cohen

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Simultaneous Turbulence Mitigation and Mode Demultiplexing using one MPLC in a Two-Mode 200-Gbit/s Free-Space OAM-Multiplexed Link.

Hao Song, Xinzhou Su, Haoqian Song, Runzhou Zhang, Zhe Zhao, Cong Liu, Kai Pang, Nanzhe Hu, Ahmed Almaiman, Shlomo Zach, Nadav Cohen, Andreas F. Molisch, Robert Boyd, Moshe Tur, Alan E. Willner

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2020

Simultaneous Orthogonalizing and Shaping of Multiple LG Beams to Mitigate Crosstalk and Power Loss by Transmitting Each of Four Data Channels on Multiple Modes in a 400-Gbit/s Free-Space Link.

Kai Pang, Haoqian Song, Xinzhou Su, Kaiheng Zou, Zhe Zhao, Hao Song, Ahmed Almaiman, Runzhou Zhang, Cong Liu, Nanzhe Hu, Shlomo Zach, Nadav Cohen, Brittany Lynn, Andreas F. Molisch, Robert W. Boyd, Moshe Tur, Alan E. Willner

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2020

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

Noam Razin, Nadav Cohen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fundamental System-Degrading Effects in THz Communications Using Multiple OAM beams With Turbulence.

Zhe Zhao, Runzhou Zhang, Hao Song, Kai Pang, Ahmed Almaiman, Huibin Zhou, Haoqian Song, Cong Liu, Nanzhe Hu, Xinzhou Su, Amir Minoofar, Shlomo Zach, Nadav Cohen, Moshe Tur, Andreas F. Molisch, Alan E. Willner

Proceedings of the 2020 IEEE International Conference on Communications, 2020

Multipath and Receiver Aperture Effects in a THz Wireless Communications Link using OAM Multiplexing.

Xinzhou Su, Runzhou Zhang, Zhe Zhao, Hao Song, Amir Minoofar, Nanzhe Hu, Huibin Zhou, Kaiheng Zou, Kai Pang, Haoqian Song, Brittany Lynn, Shlomo Zach, Nadav Cohen, Moshe Tur, Andreas F. Molisch, Hirofumi Sasaki, Doohwan Lee, Alan E. Willner

Proceedings of the IEEE Globecom Workshops, 2020

2019

Implicit Regularization in Deep Matrix Factorization.

Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

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

Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

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

Yoav Levine, Or Sharir, Nadav Cohen, Amnon Shashua

CoRR, 2018

Experimental Utilization of Repeated Spatial-Mode Shifting for Achieving Discrete Delays in a Free-Space Recirculating Loop.

Ahmed Almaiman, A. Mohajerin-Ariaei, Guodong Xie, Zhe Zhao, Yinwen Cao, Fatemeh Alishahi, Peicheng Liao, Changjing Bao, Ahmad Fallahpour, B. Shamee, Youichi Akasaka, Shlomo Zach, Nadav Cohen, Moshe Tur, Alan E. Willner

Proceedings of the Optical Fiber Communications Conference and Exposition, 2018

Coarse and Fine Continuously Tunable Optical Delay Using the Time-of-flight in Fiber Bragg Gratings and Wavelength Conversion.

Ahmed Almaiman, Yinwen Cao, A. Mohajerin-Ariaei, Fatemeh Alishahi, Ahmad Fallahpour, Dmitry Starodubov, Peicheng Liao, Changjing Bao, Shlomo Zach, Nadav Cohen, Moshe Tur, Alan E. Willner

Proceedings of the Optical Fiber Communications Conference and Exposition, 2018

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

Sanjeev Arora, Nadav Cohen, Elad Hazan

Proceedings of the 35th International Conference on Machine Learning, 2018

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

Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua

Proceedings of the 6th International Conference on Learning Representations, 2018

Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions.

Nadav Cohen, Ronen Tamari, Amnon Shashua

Proceedings of the 6th International Conference on Learning Representations, 2018

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

Assaf Shocher, Nadav Cohen, Michal Irani

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions (כותר נוסף בעברית: ניתוח ותכנון רשתות קונבולוציה על ידי פירוקי טנזורים היררכיים).

Nadav Cohen

PhD thesis, 2017

Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions.

Nadav Cohen, Or Sharir, Yoav Levine, Ronen Tamari, David Yakira, Amnon Shashua

CoRR, 2017

Inductive Bias of Deep Convolutional Networks through Pooling Geometry.

Nadav Cohen, Amnon Shashua

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Tensorial Mixture Models.

Or Sharir, Ronen Tamari, Nadav Cohen, Amnon Shashua

CoRR, 2016

Convolutional Rectifier Networks as Generalized Tensor Decompositions.

Nadav Cohen, Amnon Shashua

Proceedings of the 33nd International Conference on Machine Learning, 2016

Deep SimNets.

Nadav Cohen, Or Sharir, Amnon Shashua

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

On the Expressive Power of Deep Learning: A Tensor Analysis.

Nadav Cohen, Or Sharir, Amnon Shashua

Proceedings of the 29th Conference on Learning Theory, 2016

Controlled acoustic levitation - physical model and real-time digital implementation.

Izhak Bucher, Dotan Ilssar, Ran Gabai, Nadav Cohen, Ran Shaham, Solomon Davis

Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics, 2016

2015

In-House Solution for the RecSys Challenge 2015.

Nadav Cohen, Adi Gerzi, David Ben-Shimon, Bracha Shapira, Lior Rokach, Michael Friedmann

Proceedings of the 2015 International ACM Recommender Systems Challenge, 2015

2014

Doppler-Based Flow Rate Sensing in Microfluidic Channels.

Liron Stern, Avraham Bakal, Mor Tzur, Maya Veinguer, Noa Mazurski, Nadav Cohen, Uriel Levy

Sensors, 2014

SimNets: A Generalization of Convolutional Networks.

Nadav Cohen, Amnon Shashua

CoRR, 2014

2012

Complex Floating Point - A Novel Data Word Representation for DSP Processors.

Nadav Cohen, Shlomo Weiss

IEEE Trans. Circuits Syst. I Regul. Pap., 2012