
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_hvae")
```

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

| Model | Dataset | Metric | Obtained value | Reference value |
|:---:|:---:|:---:|:---:|:---:|
| HVAE (n_lf=4) | Binary MNIST | NLL (1000 IS) | 86.21 (0.01) | 86.40 |

[1] Samlimans, T. et al, *Markov chain monte carlo and variational inference: Bridging the gap*, ICML 2015
{"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 Table 1 in [1].



[1] Samlimans, T. et al, *Markov chain monte carlo and variational inference: Bridging the gap*, ICML 2015



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

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