Monte Carlo variational auto-encoders
Variational auto-encoders (VAE) are popular deep latent variable models which are trained by maximizing an Evidence Lower Bound (ELBO). To obtain tighter ELBO and hence better variational approximations, it has been proposed to use importance sampling to get a lower variance estimate of the evidence...
| Main Authors: | , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2021
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