Vineet John, Master’s candidate
David R. Cheriton School of Computer Science
This thesis tackles the problem of disentangling the latent style and content variables in a language modelling context. This involves splitting the latent representations of documents by learning which features of a document are discriminative of its style and content, and encoding these features separately using neural network models.
Aiman Erbad, Computer Science and Engineering Department