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dpVAEs: Fixing Sample Generation for Regularized VAEs
Unsupervised representation learning via generative modeling is a staple to many computer vision applications in the absence of labeled data. Variational Autoencoders (VAEs) are powerful generative models that learn representations useful for data generation. However, due to inherent challenges in t...
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| Publicado en: | Comput Vis ACCV |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
2021
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7993751/ https://ncbi.nlm.nih.gov/pubmed/33778815 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-69538-5_39 |
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