Tessellating the Latent Space for Non-Adversarial Generative Auto-Encoders
Non-adversarial generative models are relatively easy to train and have less mode collapse than adversarial models. However, they are not very accurate in approximating the target distribution in latent space because they don't have a discriminator. To this end, we develop a novel divide-and-co...
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 2 vom: 19. Feb., Seite 780-792 |
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| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2024
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence |
| Sujets: | Journal Article |
| Accès en ligne |
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