High-dimensional Motion Planning using Latent Variable Models via Approximate Inference.
Jung-Su HaHyeok-Joo ChaeHan-Lim ChoiPublished in: CoRR (2017)
Keyphrases
- motion planning
- approximate inference
- latent variables
- high dimensional
- probabilistic model
- mobile robot
- exact inference
- gaussian process
- variational methods
- graphical models
- humanoid robot
- posterior distribution
- random variables
- low dimensional
- prior knowledge
- expectation propagation
- dimensionality reduction
- topic models
- belief propagation
- bayesian networks
- structured prediction
- high dimensional data
- probabilistic inference
- data points
- free energy
- hidden variables
- conditional random fields
- parameter space
- message passing
- feature space
- machine learning
- bayesian learning
- pairwise
- active learning
- hidden markov models
- dynamic programming
- semi supervised