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Article

Устойчивый к шуму метод обучения вариационного автокодировщика

Variational autoencoder (VAE) is a probabilistic unsupervised method that uses deep learning. We propose a robust approach to the training of VAE using a modified likelihood function. We propose and analyze two variational lower bound objectives. The effectiveness of the method is experimentally shown by artificially introducing noise objects.