The following pages link to (Q5396726):
Displaying 26 items.
- The extended skew Gaussian process for regression (Q483499) (← links)
- Log-concavity and strong log-concavity: a review (Q485901) (← links)
- A general robust t-process regression model (Q829720) (← links)
- Laplace approximation for logistic Gaussian process density estimation and regression (Q899031) (← links)
- Energy-driven image interpolation using Gaussian process regression (Q1760690) (← links)
- A survey of Bayesian predictive methods for model assessment, selection and comparison (Q1951655) (← links)
- Robust weighted Gaussian processes (Q1995846) (← links)
- Identification of Gaussian process with switching noise mode and missing data (Q2030947) (← links)
- Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation (Q2058770) (← links)
- Factor graph fragmentization of expectation propagation (Q2131932) (← links)
- Robust manifold broad learning system for large-scale noisy chaotic time series prediction: a perturbation perspective (Q2185604) (← links)
- Leveraged least trimmed absolute deviations (Q2241912) (← links)
- Gaussian process regression with skewed errors (Q2297103) (← links)
- Laplace approximation and natural gradient for Gaussian process regression with heteroscedastic Student-\(t\) model (Q2329797) (← links)
- Robust Autoregression: Student-t Innovations Using Variational Bayes (Q4572735) (← links)
- Student-t Process Regression with Dependent Student-t Noise (Q4576167) (← links)
- Expectation Propagation in the Large Data Limit (Q4603808) (← links)
- (Q4637069) (← links)
- (Q4969101) (← links)
- (Q4999099) (← links)
- Altering Gaussian process to Student-<i>t</i> process for maximum distribution construction (Q5028003) (← links)
- (Q5054592) (← links)
- On the robustness to outliers of the Student‐t process (Q6049757) (← links)
- Variational policy search using sparse Gaussian process priors for learning multimodal optimal actions (Q6079126) (← links)
- Estimating the effects of a California gun control program with multitask Gaussian processes (Q6104087) (← links)
- Composite T-process regression models (Q6113639) (← links)
