GMVAE
Gaussian Mixture Variational Autoencoder
**GMVAE**, or **Gaussian Mixture Variational Autoencoder**, is a stochastic regularization layer for [transformers](https://paperswithcode.com/methods/category/transformers). A GMVAE layer is trained using a 700-dimensional internal representation of the first MLP layer. For every output from the first MLP layer, the GMVAE layer first computes a latent low-dimensional representation sampling from the GMVAE posterior distribution to then provide at the output a reconstruction sampled from a generative model.
Regularizing Transformers With Deep Probabilistic Layers
https://paperswithcode.com/paper/regularizing-transformers-with-deep
Regularizing Transformers With Deep Probabilistic Layers