| 2025 | ICLR | DeciMamba: Exploring the Length Extrapolation Potential of Mamba. | Assaf Ben-Kish, Itamar Zimerman, Shady Abu-Hussein, Nadav Cohen, Amir Globerson, Lior Wolf, Raja Giryes |
| 2024 | EMNLP | Data-driven Coreference-based Ontology Building. | Shir Ashury-Tahan, Amir David Nissan Cohen, Nadav Cohen, Yoram Louzoun, Yoav Goldberg |
| 2024 | ICML | 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 |
| 2023 | ICLR | Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets. | Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen, Amir Globerson |
| 2022 | AISTATS | On the Implicit Bias of Gradient Descent for Temporal Extrapolation. | Edo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson |
| 2022 | ICML | Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. | Noam Razin, Asaf Maman, Nadav Cohen |
| 2021 | ICML | Implicit Regularization in Tensor Factorization. | Noam Razin, Asaf Maman, Nadav Cohen |
| 2020 | GLOBECOM | 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 |
| 2019 | ICLR | A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks. | Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu |
| 2018 | CVPR | "Zero-Shot" Super-Resolution Using Deep Internal Learning. | Assaf Shocher, Nadav Cohen, Michal Irani |
| 2018 | ICLR | Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions. | Nadav Cohen, Ronen Tamari, Amnon Shashua |
| 2018 | ICLR | Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. | Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua |
| 2018 | ICML | On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization. | Sanjeev Arora, Nadav Cohen, Elad Hazan |
| 2017 | ICLR | Inductive Bias of Deep Convolutional Networks through Pooling Geometry. | Nadav Cohen, Amnon Shashua |
| 2016 | COLT | On the Expressive Power of Deep Learning: A Tensor Analysis. | Nadav Cohen, Or Sharir, Amnon Shashua |
| 2016 | CVPR | Deep SimNets. | Nadav Cohen, Or Sharir, Amnon Shashua |
| 2016 | ICML | Convolutional Rectifier Networks as Generalized Tensor Decompositions. | Nadav Cohen, Amnon Shashua |
| 2015 | RecSys | In-House Solution for the RecSys Challenge 2015. | Nadav Cohen, Adi Gerzi, David Ben-Shimon, Bracha Shapira, Lior Rokach, Michael Friedmann |