Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks.
Juan MaroñasRoberto ParedesDaniel RamosPublished in: CoRR (2019)
Keyphrases
- probabilistic model
- neural network
- bayesian inference
- bayesian networks
- belief nets
- graphical models
- posterior probability
- latent variables
- camera calibration
- mixture model
- generative model
- language model
- expectation maximization
- bayesian models
- conditional probabilities
- variational inference
- artificial neural networks
- posterior distribution
- neural network model
- back propagation
- probabilistic modeling
- fuzzy logic
- pattern recognition
- hidden variables
- bayesian learning
- conditional random fields
- maximum likelihood
- multilayer perceptron
- bayesian estimation
- hand eye coordination
- deep learning
- stereo camera
- genetic algorithm
- machine learning
- training process
- multi layer
- radial basis function
- topic models
- higher order
- deep belief networks