Nadav Cohen

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 60

Top Topics

Velocity Vector

Vehicle Navigation

Low Dimensional

Tensor Factorization

Top Venues

Publications

Dror Hurwitz, Nadav Cohen, Itzik Klein
Deep Learning Assisted Inertial Dead Reckoning and Fusion. CoRR (2024)
Nadav Cohen, Itzik Klein
Data-Driven Strategies for Coping with Incomplete DVL Measurements. CoRR (2024)
Nadav Cohen, Itzik Klein
A-KIT: Adaptive Kalman-Informed Transformer. CoRR (2024)
Nadav Cohen, Itzik Klein
Seamless Underwater Navigation with Limited Doppler Velocity Log Measurements. CoRR (2024)
Noam Razin, Yotam Alexander, Edo Cohen-Karlik, Raja Giryes, Amir Globerson, Nadav Cohen
Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States. CoRR (2024)
Assaf Ben-Kish, Itamar Zimerman, Shady Abu-Hussein, Nadav Cohen, Amir Globerson, Lior Wolf, Raja Giryes
DeciMamba: Exploring the Length Extrapolation Potential of Mamba. CoRR (2024)
Nadav Cohen, Itzik Klein
Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions. CoRR (2023)
Yotam Alexander, Nimrod De La Vega, Noam Razin, Nadav Cohen
What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement. CoRR (2023)
Noam Razin, Tom Verbin, Nadav Cohen
On the Ability of Graph Neural Networks to Model Interactions Between Vertices. NeurIPS (2023)
Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen, Amir Globerson
Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets. ICLR (2023)
Yotam Alexander, Nimrod De La Vega, Noam Razin, Nadav Cohen
What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement. NeurIPS (2023)
Nadav Cohen, Govind Menon, Zsolt Veraszto
Deep Linear Networks for Matrix Completion - an Infinite Depth Limit. SIAM J. Appl. Dyn. Syst. 22 (4) (2023)
Edo Cohen-Karlik, Itamar Menuhin-Gruman, Nadav Cohen, Raja Giryes, Amir Globerson
Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network. CoRR (2022)
Noam Razin, Asaf Maman, Nadav Cohen
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. CoRR (2022)
Edo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson
On the Implicit Bias of Gradient Descent for Temporal Extrapolation. AISTATS (2022)
Edo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson
On the Implicit Bias of Gradient Descent for Temporal Extrapolation. CoRR (2022)
Nadav Cohen, Itzik Klein
BeamsNet: A data-driven Approach Enhancing Doppler Velocity Log Measurements for Autonomous Underwater Vehicle Navigation. CoRR (2022)
Noam Razin, Tom Verbin, Nadav Cohen
On the Ability of Graph Neural Networks to Model Interactions Between Vertices. CoRR (2022)
Nadav Cohen, Zeev Yampolsky, Itzik Klein
Set-Transformer BeamsNet for AUV Velocity Forecasting in Complete DVL Outage Scenarios. CoRR (2022)
Nadav Cohen, Yael Newman, Ariel Shamir
Semantic Segmentation in Art Paintings. CoRR (2022)
Nadav Cohen, Itzik Klein
BeamsNet: A data-driven approach enhancing Doppler velocity log measurements for autonomous underwater vehicle navigation. Eng. Appl. Artif. Intell. 114 (2022)
Nadav Cohen, Yael Newman, Ariel Shamir
Semantic Segmentation in Art Paintings. Comput. Graph. Forum 41 (2) (2022)
Nadav Cohen, Govind Menon, Zsolt Veraszto
Deep Linear Networks for Matrix Completion - An Infinite Depth Limit. CoRR (2022)
Noam Razin, Asaf Maman, Nadav Cohen
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. ICML (2022)
Nadav Cohen, Itzik Klein
LiBeamsNet: AUV Velocity Vector Estimation in Situations of Limited DVL Beam Measurements. CoRR (2022)
Noam Razin, Asaf Maman, Nadav Cohen
Implicit Regularization in Tensor Factorization. CoRR (2021)
Noam Razin, Asaf Maman, Nadav Cohen
Implicit Regularization in Tensor Factorization. ICML (2021)
Nadav Cohen, Shauli Shmilovich, Yaniv Oiknine, Adrian Stern
Deep neural network classification in the compressively sensed spectral image domain. J. Electronic Imaging 30 (4) (2021)
Omer Elkabetz, Nadav Cohen
Continuous vs. Discrete Optimization of Deep Neural Networks. CoRR (2021)
Omer Elkabetz, Nadav Cohen
Continuous vs. Discrete Optimization of Deep Neural Networks. NeurIPS (2021)
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
Multipath and Receiver Aperture Effects in a THz Wireless Communications Link using OAM Multiplexing. GLOBECOM (Workshops) (2020)
Noam Razin, Nadav Cohen
Implicit Regularization in Deep Learning May Not Be Explainable by Norms. NeurIPS (2020)
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
Fundamental System-Degrading Effects in THz Communications Using Multiple OAM beams With Turbulence. ICC (2020)
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
Simultaneous Turbulence Mitigation and Mode Demultiplexing using one MPLC in a Two-Mode 200-Gbit/s Free-Space OAM-Multiplexed Link. OFC (2020)
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
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. OFC (2020)
Noam Razin, Nadav Cohen
Implicit Regularization in Deep Learning May Not Be Explainable by Norms. CoRR (2020)
Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo
Implicit Regularization in Deep Matrix Factorization. CoRR (2019)
Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. ICLR (Poster) (2019)
Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo
Implicit Regularization in Deep Matrix Factorization. NeurIPS (2019)
Nadav Cohen, Ronen Tamari, Amnon Shashua
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions. ICLR (2018)
Ahmed Almaiman, Yinwen Cao, A. Mohajerin-Ariaei, Fatemeh Alishahi, A. Fallahpour, Dmitry Starodubov, P. Liao, Changjing Bao, Shlomo Zach, Nadav Cohen, Moshe Tur, Alan E. Willner
Coarse and Fine Continuously Tunable Optical Delay Using the Time-of-flight in Fiber Bragg Gratings and Wavelength Conversion. OFC (2018)
Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. ICLR (Poster) (2018)
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
Experimental Utilization of Repeated Spatial-Mode Shifting for Achieving Discrete Delays in a Free-Space Recirculating Loop. OFC (2018)
Sanjeev Arora, Nadav Cohen, Elad Hazan
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization. ICML (2018)
Assaf Shocher, Nadav Cohen, Michal Irani
"Zero-Shot" Super-Resolution Using Deep Internal Learning. CVPR (2018)
Yoav Levine, Or Sharir, Nadav Cohen, Amnon Shashua
Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks. CoRR (2018)
Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. CoRR (2018)
Sanjeev Arora, Nadav Cohen, Elad Hazan
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization. CoRR (2018)
Nadav Cohen, Amnon Shashua
Inductive Bias of Deep Convolutional Networks through Pooling Geometry. ICLR (Poster) (2017)
Nadav Cohen, Or Sharir, Yoav Levine, Ronen Tamari, David Yakira, Amnon Shashua
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions. CoRR (2017)
Assaf Shocher, Nadav Cohen, Michal Irani
"Zero-Shot" Super-Resolution using Deep Internal Learning. CoRR (2017)
Nadav Cohen, Ronen Tamari, Amnon Shashua
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions. CoRR (2017)
Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. CoRR (2017)
Nadav Cohen, Amnon Shashua
Inductive Bias of Deep Convolutional Networks through Pooling Geometry. CoRR (2016)
Nadav Cohen, Or Sharir, Amnon Shashua
Deep SimNets. CVPR (2016)
Nadav Cohen, Or Sharir, Amnon Shashua
On the Expressive Power of Deep Learning: A Tensor Analysis. COLT (2016)
Nadav Cohen, Amnon Shashua
Convolutional Rectifier Networks as Generalized Tensor Decompositions. CoRR (2016)
Izhak Bucher, Dotan Ilssar, Ran Gabai, Nadav Cohen, Ran Shaham, Solomon Davis
Controlled acoustic levitation - physical model and real-time digital implementation. AIM (2016)
Nadav Cohen, Amnon Shashua
Convolutional Rectifier Networks as Generalized Tensor Decompositions. ICML (2016)
Or Sharir, Ronen Tamari, Nadav Cohen, Amnon Shashua
Tensorial Mixture Models. CoRR (2016)
Nadav Cohen, Or Sharir, Amnon Shashua
Deep SimNets. CoRR (2015)
Nadav Cohen, Adi Gerzi, David Ben-Shimon, Bracha Shapira, Lior Rokach, Michael Friedmann
In-House Solution for the RecSys Challenge 2015. RecSys Challenge (2015)
Nadav Cohen, Or Sharir, Amnon Shashua
On the Expressive Power of Deep Learning: A Tensor Analysis. CoRR (2015)
Liron Stern, Avraham Bakal, Mor Tzur, Maya Veinguer, Noa Mazurski, Nadav Cohen, Uriel Levy
Doppler-Based Flow Rate Sensing in Microfluidic Channels. Sensors 14 (9) (2014)
Nadav Cohen, Amnon Shashua
SimNets: A Generalization of Convolutional Networks. CoRR (2014)
Nadav Cohen, Shlomo Weiss
Complex Floating Point - A Novel Data Word Representation for DSP Processors. IEEE Trans. Circuits Syst. I Regul. Pap. (10) (2012)