Bridge the Inference Gaps of Neural Processes via Expectation Maximization.
Qi WangMarco FedericiHerke van HoofPublished in: ICLR (2023)
Keyphrases
- expectation maximization
- em algorithm
- gibbs sampling
- neural network
- mixture model
- network architecture
- bayesian networks
- parameter learning
- maximum likelihood estimation
- maximum likelihood
- generative model
- learning rules
- bayesian inference
- process model
- parameter estimation
- image processing
- gaussian mixture model
- random fields
- probabilistic model
- reinforcement learning
- image segmentation
- case study
- computer vision