Manifold Learning by Mixture Models of VAEs for Inverse Problems.
Giovanni S. AlbertiJohannes HertrichMatteo SantacesariaSilvia SciuttoPublished in: CoRR (2023)
Keyphrases
- manifold learning
- mixture model
- inverse problems
- image reconstruction
- global optimization
- convex optimization
- gaussian mixture model
- low dimensional
- semi supervised
- probabilistic model
- em algorithm
- dimensionality reduction
- generative model
- unsupervised learning
- model selection
- high dimensional
- density estimation
- high dimensional data
- dimension reduction
- expectation maximization
- language model
- sparse representation
- feature extraction
- smoothness constraint
- cross validation
- feature space
- partial differential equations
- maximum likelihood
- prior knowledge
- neural network
- gaussian mixture
- data mining
- feature selection
- pairwise
- optical flow
- data sets