Towards Unsupervised Classification with Deep Generative Models

no code implementations • ICLR 2018 • Dimitris Kalatzis, Konstantia Kotta, Ilias Kalamaras, Anastasios Vafeiadis, Andrew Rawstron, Dimitris Tzovaras, Kostas Stamatopoulos

Deep generative models have advanced the state-of-the-art in semi-supervised classification, however their capacity for deriving useful discriminative features in a completely unsupervised fashion for classification in difficult real-world data sets, where adequate manifold separation is required has not been adequately explored.

Classification Clustering +1