Skip to content
No description, website, or topics provided.
Python
Branch: master
Clone or download
Latest commit 746e3cb Jul 19, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
data first commit Apr 29, 2019
experiments first commit Apr 29, 2019
pvae first commit Apr 29, 2019
tests
.gitignore
LICENSE.md
README.md Update README.md Jul 19, 2019
requirements.txt
setup.py

README.md

Hierarchal Representations with Poincaré Variational Auto-Encoders

Prerequisites

Modules in requirements.txt.

Run experiments

Synthetic dataset

CUDA_VISIBLE_DEVICES='' python3 pvae/main.py --model hyp_tree --latent-dim 2 --hidden-dim 200 --prior-std-scale 1.7 --data-dim 50 --data-params 6 2 1 1 5 5 --arch-dec Gyroplane --epochs 1000 --save-freq 1000 --lr 1e-3 --batch-size 64 --iwae-samples 5000

MNIST dataset

CUDA_VISIBLE_DEVICES='' python3 pvae/main.py --model hyp_mnist --latent-dim 2 --hidden-dim 600 --c 0.7 --prior WrappedNormal --posterior WrappedNormal --arch-dec Gyroplane --arch-enc '' --lr 5e-4 --epochs 80 --save-freq 80 --batch-size 128 --iwae-samples 5000

Running tests

pip3 install nose2
nose2

References

If you find this code useful for your research, please cite the following paper in your publication:

@article{mathieu2019poincare,
  title={Hierarchical Representations with Poincar\'e Variational Auto-Encoders},
  author={Mathieu, Emile and Le Lan, Charline and Maddison, Chris J. and Tomioka, Ryota and Whye Teh, Yee},
  journal={arXiv preprint arXiv:1901.06033},
  year={2019}
}
You can’t perform that action at this time.