Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems

Overview

Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems

This repository is the official implementation of Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems (include link to NEURIPS paper here).

Requirements

All of the requirements are already installed in the Google Colab environment (https://colab.research.google.com/) in the Colab notebooks provided. This is the recommended environment to use these notebooks.

To run the code on your own machine you will need to install JAX (https://github.com/google/jax#installation).

Training and Evaluation

Instructions for how to train and evaluate the models for the 3-bit memory task and the context-dependent integration task are included in the Colab notebooks : JSLDS_3bit_memory_notebook.ipynb and JSLDS_context_integration_notebook.ipynb.

Pre-trained Models

We include pre-trained weights for both the co-trained models as well as the standard models without JSLDS co-training for both the 3-bit memory task and the context-dependent integration task.

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