Model checkpoints can be downloaded from releases.
Use the argument --resume [checkpt.pth] to evaluate or sample from the model.
Each checkpoint contains two sets of parameters, one from training and one containing the exponential moving average (EMA) accumulated over the course of training. Scripts will automatically use the EMA parameters for evaluation and sampling.
BibTeX
@inproceedings{chen2019residualflows,
title={Residual Flows for Invertible Generative Modeling},
author={Chen, Ricky T. Q. and Behrmann, Jens and Duvenaud, David and Jacobsen, J{"{o}}rn{-}Henrik},
booktitle = {Advances in Neural Information Processing Systems},
year={2019}
}