Code package synapsegan implementing method and experiments described in the associated manuscript "Indistinguishable network dynamics can emerge from unalike plasticity rules"
With a working Python environment, install synapsegan using pip:
pip install "git+https://github.com/mackelab/synapsegan"
The paper describes results for experiments with Oja's Rule and a rate network, and fitting GANs to data generated from the former, with different parametrizations of the plasticity rule.
Code for setting up GAN networks, any other pre-/post-processing code, and the hyperparameter settings for the experiments is available inside tasks/.
To reproduce the experiments, change the configuration settings for the appropriate experiment in tasks/, and use the run.py script from the repository's root directory (note that this relies on wandb to log experiments):
python run.py --task_name TASK_NAME
where TASK_NAME can be oja_net_small, oja_net_noise_small OR oja_net_big
Note that we do not provide training data for these experiments. However, users can generate training data using syngan.utils.make_training_data.make_training_test_datasets.
Code to reproduce the figures in the paper is available in plotting_code. However this is only code: the data required to run it will be provided upon request.