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Anders Boesen Lindbo Larsen

2 accepted papers

2016

Autoencoding beyond pixels using a learned similarity metric

ICML 2016poster

We present an autoencoder that leverages learned representations to better measure similarities in data space. By combining a variational autoencoder (VAE) with a generative adversarial network (GAN) we can use learned feature representations in the GAN discriminator as basis for the VAE reconstruct…

2016

Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation

AISTATS 2016poster

Data augmentation is a key element in training high-dimensional models. In this approach, one synthesizes new observations by applying pre-specified transformations to the original training data; e.g. new images are formed by rotating old ones. Current augmentation schemes, however, rely on ma…

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