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beta-vae-normalizing-flows
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README.md
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* refer to other directories first if you don't want to take a fast-track * refer to other directories first if you don't want to take a fast-track
* Noisy moons * Noisy moons
* initial test data; [see usage](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.make_moons.html) * initial test data - [see usage](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.make_moons.html)
* Thoracic surgery * Thoracic surgery
* current test data; [find out more](https://www.kaggle.com/sid321axn/thoraric-surgery) * current test data - [find out more](https://www.kaggle.com/sid321axn/thoraric-surgery)
* Beta-VAE * Beta-VAE
* variational autoencoder algorithm extended with a beta parameter to put implicit pressure on the learnt posterior * variational autoencoder algorithm extended with a beta parameter to put implicit pressure on the learnt posterior
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* Poisson * Poisson
* MAE * MAE
* Cross Entropy * Cross Entropy
* Statistical measures are in progress, ex. CI's, p-values, etc. if needed * Statistical measures are in progress - ex. CI's, p-values, etc. if needed
### References ### References
* Rezende, D. J., & Mohamed, S. (2015). [Variational Inference with Normalizing Flows.](https://arxiv.org/abs/1505.05770v6) * Rezende, D. J., & Mohamed, S. (2015). [Variational Inference with Normalizing Flows.](https://arxiv.org/abs/1505.05770v6)
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