This repository contains the implementation of the following models:
- Wassertein GAN: Gulrajani, Ishaan, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville. "Improved Training of Wasserstein GANs." Advances in Neural Information Processing Systems, March 31, 2017, 5768–78. http://arxiv.org/abs/1704.00028.
- Autoencoder with support to multiple feature types. Autoencoder loss may be masked to avoid applying gradient-based optimisation for specific features per example. One possible application is to avoid training model to replicate imputed data.
© 2020 WTFPL - Werner Spolidoro Freund
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