default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDNadav Cohen
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c27]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. ICML 2024- [i35]Nadav Cohen, Itzik Klein:
A-KIT: Adaptive Kalman-Informed Transformer. CoRR abs/2401.09987 (2024) - [i34]Nadav Cohen, Itzik Klein:
Data-Driven Strategies for Coping with Incomplete DVL Measurements. CoRR abs/2401.15620 (2024) - [i33]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 abs/2402.07875 (2024) - [i32]Nadav Cohen, Itzik Klein:
Seamless Underwater Navigation with Limited Doppler Velocity Log Measurements. CoRR abs/2404.13742 (2024) - [i31]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 abs/2406.14528 (2024) - [i30]Dror Hurwitz, Nadav Cohen, Itzik Klein:
Deep Learning Assisted Inertial Dead Reckoning and Fusion. CoRR abs/2407.16387 (2024) - [i29]Nadav Cohen, Noam Razin:
Lecture Notes on Linear Neural Networks: A Tale of Optimization and Generalization in Deep Learning. CoRR abs/2408.13767 (2024) - 2023
- [j6]Nadav Cohen, Govind Menon, Zsolt Veraszto:
Deep Linear Networks for Matrix Completion - an Infinite Depth Limit. SIAM J. Appl. Dyn. Syst. 22(4): 3208-3232 (2023) - [c26]Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen, Amir Globerson:
Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets. ICLR 2023 - [c25]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 - [c24]Noam Razin, Tom Verbin, Nadav Cohen:
On the Ability of Graph Neural Networks to Model Interactions Between Vertices. NeurIPS 2023 - [i28]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 abs/2303.11249 (2023) - [i27]Nadav Cohen
, Itzik Klein:
Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions. CoRR abs/2307.00014 (2023) - 2022
- [j5]Nadav Cohen, Yael Newman, Ariel Shamir:
Semantic Segmentation in Art Paintings. Comput. Graph. Forum 41(2): 261-275 (2022) - [j4]Nadav Cohen, Itzik Klein:
BeamsNet: A data-driven approach enhancing Doppler velocity log measurements for autonomous underwater vehicle navigation. Eng. Appl. Artif. Intell. 114: 105216 (2022) - [c23]Edo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson:
On the Implicit Bias of Gradient Descent for Temporal Extrapolation. AISTATS 2022: 10966-10981 - [c22]Noam Razin, Asaf Maman, Nadav Cohen:
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. ICML 2022: 18422-18462 - [i26]Noam Razin, Asaf Maman, Nadav Cohen:
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. CoRR abs/2201.11729 (2022) - [i25]Edo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson:
On the Implicit Bias of Gradient Descent for Temporal Extrapolation. CoRR abs/2202.04302 (2022) - [i24]Nadav Cohen, Yael Newman, Ariel Shamir:
Semantic Segmentation in Art Paintings. CoRR abs/2203.03238 (2022) - [i23]Nadav Cohen, Itzik Klein:
BeamsNet: A data-driven Approach Enhancing Doppler Velocity Log Measurements for Autonomous Underwater Vehicle Navigation. CoRR abs/2206.13603 (2022) - [i22]Nadav Cohen, Itzik Klein:
LiBeamsNet: AUV Velocity Vector Estimation in Situations of Limited DVL Beam Measurements. CoRR abs/2210.11572 (2022) - [i21]Nadav Cohen, Govind Menon, Zsolt Veraszto:
Deep Linear Networks for Matrix Completion - An Infinite Depth Limit. CoRR abs/2210.12497 (2022) - [i20]Edo Cohen-Karlik, Itamar Menuhin-Gruman, Nadav Cohen, Raja Giryes, Amir Globerson:
Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network. CoRR abs/2210.14064 (2022) - [i19]Noam Razin, Tom Verbin, Nadav Cohen:
On the Ability of Graph Neural Networks to Model Interactions Between Vertices. CoRR abs/2211.16494 (2022) - [i18]Nadav Cohen, Zeev Yampolsky, Itzik Klein:
Set-Transformer BeamsNet for AUV Velocity Forecasting in Complete DVL Outage Scenarios. CoRR abs/2212.11671 (2022) - 2021
- [j3]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) - [c21]Noam Razin, Asaf Maman, Nadav Cohen:
Implicit Regularization in Tensor Factorization. ICML 2021: 8913-8924 - [c20]Omer Elkabetz, Nadav Cohen:
Continuous vs. Discrete Optimization of Deep Neural Networks. NeurIPS 2021: 4947-4960 - [i17]Noam Razin, Asaf Maman, Nadav Cohen:
Implicit Regularization in Tensor Factorization. CoRR abs/2102.09972 (2021) - [i16]Omer Elkabetz, Nadav Cohen:
Continuous vs. Discrete Optimization of Deep Neural Networks. CoRR abs/2107.06608 (2021) - 2020
- [c19]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: 1-6 - [c18]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: 1-7 - [c17]Noam Razin, Nadav Cohen:
Implicit Regularization in Deep Learning May Not Be Explainable by Norms. NeurIPS 2020 - [c16]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: 1-3 - [c15]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: 1-3 - [i15]Noam Razin, Nadav Cohen:
Implicit Regularization in Deep Learning May Not Be Explainable by Norms. CoRR abs/2005.06398 (2020)
2010 – 2019
- 2019
- [c14]Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu:
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. ICLR (Poster) 2019 - [c13]Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo:
Implicit Regularization in Deep Matrix Factorization. NeurIPS 2019: 7411-7422 - [i14]Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo:
Implicit Regularization in Deep Matrix Factorization. CoRR abs/1905.13655 (2019) - 2018
- [c12]Assaf Shocher, Nadav Cohen, Michal Irani:
"Zero-Shot" Super-Resolution Using Deep Internal Learning. CVPR 2018: 3118-3126 - [c11]Nadav Cohen, Ronen Tamari, Amnon Shashua:
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions. ICLR 2018 - [c10]Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua:
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. ICLR (Poster) 2018 - [c9]Sanjeev Arora, Nadav Cohen, Elad Hazan:
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization. ICML 2018: 244-253 - [c8]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:
Coarse and Fine Continuously Tunable Optical Delay Using the Time-of-flight in Fiber Bragg Gratings and Wavelength Conversion. OFC 2018: 1-3 - [c7]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: 1-3 - [i13]Sanjeev Arora, Nadav Cohen, Elad Hazan:
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization. CoRR abs/1802.06509 (2018) - [i12]Yoav Levine, Or Sharir, Nadav Cohen, Amnon Shashua:
Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks. CoRR abs/1803.09780 (2018) - [i11]Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu:
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. CoRR abs/1810.02281 (2018) - 2017
- [b1]Nadav Cohen:
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions (כותר נוסף בעברית: ניתוח ותכנון רשתות קונבולוציה על ידי פירוקי טנזורים היררכיים). Hebrew University of Jerusalem, Israel, 2017 - [c6]Nadav Cohen, Amnon Shashua:
Inductive Bias of Deep Convolutional Networks through Pooling Geometry. ICLR (Poster) 2017 - [i10]Nadav Cohen, Ronen Tamari, Amnon Shashua:
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions. CoRR abs/1703.06846 (2017) - [i9]Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua:
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. CoRR abs/1704.01552 (2017) - [i8]Nadav Cohen, Or Sharir, Yoav Levine, Ronen Tamari, David Yakira, Amnon Shashua:
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions. CoRR abs/1705.02302 (2017) - [i7]Assaf Shocher, Nadav Cohen, Michal Irani:
"Zero-Shot" Super-Resolution using Deep Internal Learning. CoRR abs/1712.06087 (2017) - 2016
- [c5]Izhak Bucher, Dotan Ilssar, Ran Gabai, Nadav Cohen, Ran Shaham, Solomon Davis:
Controlled acoustic levitation - physical model and real-time digital implementation. AIM 2016: 452-456 - [c4]Nadav Cohen, Or Sharir, Amnon Shashua:
On the Expressive Power of Deep Learning: A Tensor Analysis. COLT 2016: 698-728 - [c3]Nadav Cohen, Or Sharir, Amnon Shashua:
Deep SimNets. CVPR 2016: 4782-4791 - [c2]Nadav Cohen, Amnon Shashua:
Convolutional Rectifier Networks as Generalized Tensor Decompositions. ICML 2016: 955-963 - [i6]Nadav Cohen, Amnon Shashua:
Convolutional Rectifier Networks as Generalized Tensor Decompositions. CoRR abs/1603.00162 (2016) - [i5]Nadav Cohen, Amnon Shashua:
Inductive Bias of Deep Convolutional Networks through Pooling Geometry. CoRR abs/1605.06743 (2016) - [i4]Or Sharir, Ronen Tamari, Nadav Cohen, Amnon Shashua:
Tensorial Mixture Models. CoRR abs/1610.04167 (2016) - 2015
- [c1]Nadav Cohen, Adi Gerzi, David Ben-Shimon, Bracha Shapira, Lior Rokach, Michael Friedmann:
In-House Solution for the RecSys Challenge 2015. RecSys Challenge 2015: 10:1-10:4 - [i3]Nadav Cohen, Or Sharir, Amnon Shashua:
Deep SimNets. CoRR abs/1506.03059 (2015) - [i2]Nadav Cohen, Or Sharir, Amnon Shashua:
On the Expressive Power of Deep Learning: A Tensor Analysis. CoRR abs/1509.05009 (2015) - 2014
- [j2]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): 16799-16807 (2014) - [i1]Nadav Cohen, Amnon Shashua:
SimNets: A Generalization of Convolutional Networks. CoRR abs/1410.0781 (2014) - 2012
- [j1]Nadav Cohen, Shlomo Weiss:
Complex Floating Point - A Novel Data Word Representation for DSP Processors. IEEE Trans. Circuits Syst. I Regul. Pap. 59-I(10): 2252-2262 (2012)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-30 00:58 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
