Self-explaining variational posterior distributions for Gaussian Process models.
Sarem SeitzPublished in: CoRR (2021)
Keyphrases
- posterior distribution
- gaussian process models
- gaussian process
- hyperparameters
- latent variables
- gaussian processes
- bayesian framework
- model selection
- closed form
- probability distribution
- bayesian inference
- cross validation
- image segmentation
- parameter estimation
- support vector
- maximum a posteriori
- noise level
- maximum likelihood
- random sampling
- human pose estimation
- prior information
- em algorithm
- incremental learning
- probabilistic model
- optical flow
- sample size
- incomplete data
- missing values
- posterior probability
- random variables
- variational methods
- prior knowledge
- motion estimation
- image reconstruction
- generative model
- expectation maximization