The code is organized into two parts. The first part is for synthetic experiments, while the second one is for experiments on Cifar10. See below for more information
First use pip install to install the package, as well as the corresponding dependencies, including sonnet, tensorflow, etc.
pip install -e .
Here is a simple example to use ADE for recovering parameters from a multivariate gaussian distribution.
cd ade/experiments/mvn_unimodal
./run_ade.sh
We here show a script for moons dataset. You can modify it for other datasets with different parameters.
cd ade/experiments/toy_family
./run_moons.sh
Please see ade_cifar
folder for more information.