Training Variational Autoencoders with Discrete Latent Variables Using Importance Sampling.
Alexander BartlerFelix WiewelLukas MauchBin YangPublished in: EUSIPCO (2019)
Keyphrases
- latent variables
- importance sampling
- approximate inference
- posterior distribution
- structural svms
- probabilistic model
- monte carlo
- gaussian process
- markov chain monte carlo
- latent variable models
- prior knowledge
- random variables
- particle filter
- topic models
- denoising
- markov chain
- image segmentation
- kalman filter
- graphical models
- training set
- particle filtering
- probability distribution