Regularization
Discriminative Regularization
Introduced by Lamb et al. in Discriminative Regularization for Generative ModelsDiscriminative Regularization is a regularization technique for variational autoencoders that uses representations from discriminative classifiers to augment the 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.
Source: Discriminative Regularization for Generative Models
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
