Masked Autoregressive Flow for Density Estimation
Code for reproducing the experiments in the paper:
How to run the code
To run all experiments for a particular dataset, run:
python run_experiments.py <dataset>
This will train and save all models associated with that dataset.
To evaluate all trained models and collect the results in a text file, run:
python collect_results.py <dataset>
In the above commands,
<dataset> can be any of the following:
You can use the commands with more than one datasets as arguments separated by a space, for example:
python run_experiments.py mnist cifar10 python collect_results.py mnist cifar10
How to get the datasets
- Downdload the datasets from: https://zenodo.org/record/1161203#.Wmtf_XVl8eN
- Unpack the downloaded file, and place it in the same folder as the code.
- Make sure the code reads from the location the datasets are saved at.
- Run the code as described above.
All datasets used in the experiments are preprocessed versions of public datasets. None of them belongs to us. The original datasets are: