Recognition by Variance: Learning Rules for Spatiotemporal Patterns. - Omri Barak; Misha Tsodyks (Neural Comput., 2006)

Persistent Activity in Neural Networks with Dynamic Synapses. - Omri Barak; Misha Tsodyks (PLoS Comput. Biol., 2007)

Correction: Persistent Activity in Neural Networks with Dynamic Synapses. - Omri Barak; Misha Tsodyks (PLoS Comput. Biol., 2007)

Slow oscillations in neural networks with facilitating synapses. - Ofer Melamed; Omri Barak; Gilad Silberberg; Henry Markram; Misha Tsodyks (J. Comput. Neurosci., 2008)

A Simple Derivation of a Bound on the Perceptron Margin Using Singular Value Decomposition. - Omri Barak; Mattia Rigotti (Neural Comput., 2011)

The importance of mixed selectivity in complex cognitive tasks. - Mattia Rigotti; Omri Barak; Melissa R. Warden; Xiao-Jing Wang; Nathaniel D. Daw; Earl K. Miller; Stefano Fusi (Nat., 2013)

Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks. - David Sussillo; Omri Barak (Neural Comput., 2013)

A New Approach to Model Pitch Perception Using Sparse Coding. - Oded Barzelay; Miriam Furst; Omri Barak (PLoS Comput. Biol., 2017)

Understanding and Controlling Memory in Recurrent Neural Networks. - Doron Haviv; Alexander Rivkind; Omri Barak (ICML, 2019)

Repeated sequential learning increases memory capacity via effective decorrelation in a recurrent neural network. - Tomoki Kurikawa; Omri Barak; Kunihiko Kaneko (CoRR, 2019)

One Step Back, Two Steps Forward: Interference and Learning in Recurrent Neural Networks. - Chen Beer; Omri Barak (Neural Comput., 2019)

Implementing Inductive bias for different navigation tasks through diverse RNN attrractors. - Tie Xu; Omri Barak (ICLR, 2020)

The interplay between randomness and structure during learning in RNNs. - Friedrich Schüßler; Francesca Mastrogiuseppe; Alexis M. Dubreuil; Srdjan Ostojic; Omri Barak (NeurIPS, 2020)

Scale free topology as an effective feedback system. - Alexander Rivkind; Hallel Schreier; Naama Brenner; Omri Barak (PLoS Comput. Biol., 2020)

Charting and Navigating the Space of Solutions for Recurrent Neural Networks. - Elia Turner; Kabir V. Dabholkar; Omri Barak (NeurIPS, 2021)

Mapping Low-Dimensional Dynamics to High-Dimensional Neural Activity: A Derivation of the Ring Model From the Neural Engineering Framework. - Omri Barak; Sandro Romani (Neural Comput., 2021)

The Simplicity Bias in Multi-Task RNNs: Shared Attractors, Reuse of Dynamics, and Geometric Representation. - Elia Turner; Omri Barak (NeurIPS, 2023)

When predict can also explain: few-shot prediction to select better neural latents. - Kabir V. Dabholkar; Omri Barak (CoRR, 2024)

Revealing and reshaping attractor dynamics in large networks of cortical neurons. - Chen Beer; Omri Barak (PLoS Comput. Biol., 2024)

Trained recurrent neural networks develop phase-locked limit cycles in a working memory task. - Matthijs Pals; Jakob H. Macke; Omri Barak (PLoS Comput. Biol., 2024)

Learning Dynamics of RNNs in Closed-Loop Environments. - Yoav Ger; Omri Barak (CoRR, 2025)

Finding separatrices of dynamical flows with Deep Koopman Eigenfunctions. - Kabir V. Dabholkar; Omri Barak (CoRR, 2025)