cd experiments

python -u train.py \
    --config  configs/cifar10/glow-gaussian-uni.json \
    --epochs 15000 --valid_epochs 10
    --batch_size 512 --batch_steps 2 --eval_batch_size 1000 --init_batch_size 2048 \
    --lr 0.001 --beta1 0.9 --beta2 0.999 --eps 1e-8 --warmup_steps 50 --weight_decay 1e-6 --grad_clip 0 \
    --image_size 32 --n_bits 8 \
    --data_path <data path> --model_path <model path>

@InProceedings{decoupling2021,
    title = {Decoupling Global and Local Representations via Invertible Generative Flows},
    author = {Ma, Xuezhe and Kong, Xiang and Zhang, Shanghang and Hovy, Eduard},
    booktitle = {Proceedings of the 9th International Conference on Learning Representations (ICLR-2021)},
    year = {2021},
    month = {May},
}
@incollection{macow2019,
    title = {MaCow: Masked Convolutional Generative Flow},
    author = {Ma, Xuezhe and Kong, Xiang and Zhang, Shanghang and Hovy, Eduard},
    booktitle = {Advances in Neural Information Processing Systems 33, (NeurIPS-2019)},
    year = {2019},
    publisher = {Curran Associates, Inc.}
}