README.md

Gaussian Latent Variable Model runs

You can either run the respective files in an interactive window, e.g. in VS Code or via commandline: e.g.

ipython 02_GLVM_paper_figures.py

Prior to running any of the experiments, first generate the GLVM training, test and validation dataset, that will then be used when running ../scripts/run_GLVM.py.

Run the ipython files in the following order:

1. generate the dataset using 00_GLVM_generate_dataset.py
2. start the actual training run by starting the bash script bash run_GLVM_many_seeds.sh in the bash folder or simply via running python scripts/run_GLVM.py from the base directory.
3. aggegrate the data across many runs using 01_GLVM_data_aggregation.py
4. Finally, you can run the paper analysis with 02_GLVM_paper_figures.py

Training Example

To gain an intuition for the steps required when training masked VAEs, see 03_GLVM_example_masked_VAE.ipynb.

Monkey reach task and fly walking behavior

Note: Scripts for training the VAEs and generating the figures and download links to the data will come soon!