A VAE extended with a classifier head and a combined reconstruction-plus-classification loss improves semi-supervised classification and, for most classes, anomaly detection on MNIST, Fashion-MNIST, and UCI-HAR.
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Augmenting Variational Autoencoders with Sparse Labels: A Unified Framework for Unsupervised, Semi-(un)supervised, and Supervised Learning
A VAE extended with a classifier head and a combined reconstruction-plus-classification loss improves semi-supervised classification and, for most classes, anomaly detection on MNIST, Fashion-MNIST, and UCI-HAR.