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--- |
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language: en |
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tags: |
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- pythae |
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- reproducibility |
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license: apache-2.0 |
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--- |
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### Downloading this model from the Hub |
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This model was trained with pythae. It can be downloaded or reloaded using the method `load_from_hf_hub` |
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```python |
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>>> from pythae.models import AutoModel |
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>>> model = AutoModel.load_from_hf_hub(hf_hub_path="clementchadebec/reproduced_aae") |
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``` |
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## Reproducibility |
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This trained model reproduces the results of Table 1 in [1]. |
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| Model | Dataset | Metric | Obtained value | Reference value | |
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|:---:|:---:|:---:|:---:|:---:| |
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| AAE | CELEBA 64 | FID | 43.3 | 42 | |
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[1] Tolstikhin, O Bousquet, S Gelly, and B Schölkopf. Wasserstein auto-encoders. In 6th International Conference on Learning Representations (ICLR 2018), 2018. |
