Variational Autoencoders For Semi-Supervised Deep Metric Learning

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Nathan Safir, Meekail Zain, Curtis Godwin, Eric Miller, Bella Humphrey, Shannon P. Quinn

Published: 01 Jan 2022, Last Modified: 31 Jul 2025SciPy 2022EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Deep metric learning (DML) methods generally do not incorporate unlabelled data. We propose borrowing components of the variational autoencoder (VAE) methodology to extend DML methods to train on semi-supervised datasets.