On the fairness of disentangled representations
Recently there has been a significant interest in learning disentangled representations, as they promise increased interpretability, generalization to unseen scenarios and faster learning on downstream tasks. In this paper, we investigate the usefulness of different notions of disentanglement for im...
| Main Authors: | , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
NeurIPS
2019
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