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reproduced_svae
clementchadebec/reproduced_svae
reproduced_svae is a machine learning model from clementchadebec. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pythae. The card lists the license as apache-2.0.
This model was trained with pythae. It can be downloaded or reloaded using the method loadfromhfhub
Access
Public
Updated Sep 6, 2022
Repo size
7.6 MB
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1
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Repo makeup
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.pkl1.9 MB · 50%
At a glance
- Library
- pythae
- License
- apache-2.0
- Access
- Public
- Created
- Aug 19, 2022
- Updated
- Sep 6, 2022
- SHA
- dffde818
Model card
From the Hugging Face model README
This model was trained with pythae. It can be downloaded or reloaded using the method load_from_hf_hub
>>> from pythae.models import AutoModel
>>> model = AutoModel.load_from_hf_hub(hf_hub_path="clementchadebec/reproduced_svae")
Reproducibility
This trained model reproduces the results of Table 1 in [1].
| Model | Dataset | Metric | Obtained value | Reference value |
|---|---|---|---|---|
| SVAE | Dyn. Binarized MNIST | NLL (500 IS) | 93.13 (0.01) | 93.16 (0.31) |
[1] Tim R Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, and Jakub M Tomczak. Hyperspherical variational auto-encoders. In 34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018, pages 856–865. Association For Uncertainty in Artificial Intelligence (AUAI), 2018.
- Library
- pythae
- License
- apache-2.0
- Languages
- en
- Created
- Aug 19, 2022
- Updated
- Sep 6, 2022