
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_vae")
```

## Reproducibility
This trained model reproduces the results of the VAE used in Table 1 in [1].

| Model | Dataset | Metric | Obtained value | Reference value |
|:---:|:---:|:---:|:---:|:---:|
| VAE | Binary MNIST | NLL (200 IS) | 89.78 (0.01) | 89.9 |

[1] Danilo Rezende and Shakir Mohamed. Variational inference with normalizing flows. In International Conference on Machine Learning, pages 1530–1538. PMLR, 2015
{"language": "en", "license": "apache-2.0", "library_name": "pythae", "tags": ["pythae", "reproducibility"]}
pythae reproducibility en license:apache-2.0 region:us
TAGS
#pythae #reproducibility #en #license-apache-2.0 #region-us 

This model was trained with pythae. It can be downloaded or reloaded using the method 'load\_from\_hf\_hub'


Reproducibility
---------------


This trained model reproduces the results of the VAE used in Table 1 in [1].



[1] Danilo Rezende and Shakir Mohamed. Variational inference with normalizing flows. In International Conference on Machine Learning, pages 1530–1538. PMLR, 2015



TAGS
#pythae #reproducibility #en #license-apache-2.0 #region-us 

passage: TAGS
#pythae #reproducibility #en #license-apache-2.0 #region-us 
