git clone https://github.com/vrvrv/Variational-Inference-with-Normalizing-Flows.git
cd Variational-Inference-with-Normalizing-Flows
# pip install -r requirements.txt
You can find configuration files at configs/experiment/. In our code, wandb is the default logger. So, before running code, please sign up wandb.
If you want to control the number of hidden dimension, add model.D=<hidden_dim>
.
python train.py experiment=mnist_nfvae model.D=10
We compared Vanila-VAE and NFVAE on several different settings.
We sampled from the model by taking decoder after generating gaussian noise.
Model | Negative log-likelihood |
---|---|
VAE | ~ 110.98 |
NFVAE (D=10) | ~ 109.73 |