readme: ---
  language: en
  tags:
  - pythae
  - reproducibility
  license: apache-2.0
  ---
  
  This model was trained with pythae. It can be downloaded or reloaded using the method `load_from_hf_hub`
  ```python
  >>> from pythae.models import AutoModel
  >>> model = AutoModel.load_from_hf_hub(hf_hub_path="clementchadebec/reproduced_wrapped_poincare_vae")
  ```
  
  ## Reproducibility
  This trained model reproduces the results of the official implementation of [1].
  
  | Model | Dataset | Metric | Obtained value | Reference value |
  |:---:|:---:|:---:|:---:|:---:|
  | PoincareVAE | MNIST | NLL (500 IS) | 101.66 (0.00) | 101.47 (0.01) |
  
  [1] Mathieu, E., Le Lan, C., Maddison, C. J., Tomioka, R., & Teh, Y. W. (2019). Continuous hierarchical representations with poincaré variational auto-encoders. Advances in neural information processing systems, 32.