Discriminative Regularization
Discriminative Regularization
**Discriminative Regularization** is a regularization technique for [variational autoencoders](https://paperswithcode.com/methods/category/likelihood-based-generative-models) that uses representations from discriminative classifiers to augment the [VAE](https://paperswithcode.com/method/vae) objective function (the lower bound) corresponding to a generative model. Specifically, it encourages the model’s reconstructions to be close to the data example in a representation space defined by the hidden layers of highly-discriminative, neural network based classifiers.
Discriminative Regularization for Generative Models
https://paperswithcode.com/paper/discriminative-regularization-for-generative
Discriminative Regularization for Generative Models