
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_rae_l2")
```

## Reproducibility
This trained model reproduces the results of the official implementation of [1].

| Model | Dataset | Metric | Obtained value | Reference value |
|:---:|:---:|:---:|:---:|:---:|
| RAE_L2 | MNIST | FID | 9.1 | 9.9 |

[1] Partha Ghosh, Mehdi SM Sajjadi, Antonio Vergari, Michael Black, and Bernhard Schölkopf. From variational to deterministic autoencoders. In 8th International Conference on Learning Representations, ICLR 2020, 2020.
{"language": "en", "license": "apache-2.0", "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 official implementation of [1].



[1] Partha Ghosh, Mehdi SM Sajjadi, Antonio Vergari, Michael Black, and Bernhard Schölkopf. From variational to deterministic autoencoders. In 8th International Conference on Learning Representations, ICLR 2020, 2020.



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

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