Pages that link to "Item:Q2665113"
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The following pages link to Online Bayesian inference and learning of Gaussian-process state-space models (Q2665113):
Displaying 9 items.
- Online model learning of buildings using stochastic hybrid systems based on Gaussian processes (Q1794156) (← links)
- Online learning of both state and dynamics using ensemble Kalman filters (Q2072638) (← links)
- Online inference with multi-modal likelihood functions (Q2073695) (← links)
- A flexible state-space model for learning nonlinear dynamical systems (Q2407186) (← links)
- Markov chain Monte Carlo based adaptive Rauch-Tung-Striebel smoother (Q2676154) (← links)
- Online model selection based on the variational Bayes (Q2746422) (← links)
- Strongly consistent online forecasting of centered Gaussian processes (Q4544831) (← links)
- Estimation of dual‐mode nonlinear stochastic systems with unknown parameters (Q6139888) (← links)
- An LMI framework for contraction-based nonlinear control design by derivatives of Gaussian process regression (Q6164037) (← links)