Pages that link to "Item:Q781985"
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The following pages link to Gaussian process regression and conditional polynomial chaos for parameter estimation (Q781985):
Displaying 11 items.
- Multi-fidelity Gaussian process regression for prediction of random fields (Q1685592) (← links)
- Nested polynomial trends for the improvement of Gaussian process-based predictors (Q1691892) (← links)
- Properties of the Bayesian parameter estimation of a regression based on Gaussian processes (Q2259293) (← links)
- On the construction of uncertain time series surrogates using polynomial chaos and Gaussian processes (Q2292255) (← links)
- Physics-informed Karhunen-Loéve and neural network approximations for solving inverse differential equation problems (Q2671323) (← links)
- A gaussian process with parabolic covariances (Q3988132) (← links)
- (Q4027711) (← links)
- A Gaussian Process Regression Model for Distribution Inputs (Q4682941) (← links)
- (Q5405251) (← links)
- Physics-informed machine learning method with space-time Karhunen-Loève expansions for forward and inverse partial differential equations (Q6196622) (← links)
- Randomized physics-informed machine learning for uncertainty quantification in high-dimensional inverse problems (Q6639314) (← links)
