State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations.
Zheng ZhaoFilip TronarpRoland HostettlerSimo SärkkäPublished in: ICASSP (2020)
Keyphrases
- gaussian process
- state space
- stochastic differential equations
- regression model
- maximum a posteriori estimation
- hyperparameters
- model selection
- bayesian framework
- latent variables
- semi supervised
- approximate inference
- poisson process
- brownian motion
- reinforcement learning
- state variables
- cross validation
- markov chain
- dynamic programming
- optimal policy
- reproducing kernel hilbert space
- fractional brownian motion
- image segmentation
- bayesian inference