The following pages link to (Q3394879):
Displaying 50 items.
- A comparative evaluation of stochastic-based inference methods for Gaussian process models (Q399908) (← links)
- Predicting articulated human motion from spatial processes (Q409100) (← links)
- Model selection in reinforcement learning (Q415618) (← links)
- Probabilistic models and uncertainty quantification for the ionization reaction rate of atomic nitrogen (Q417937) (← links)
- A tutorial on Bayesian nonparametric models (Q423105) (← links)
- Approximate Bayesian inference for large spatial datasets using predictive process models (Q434887) (← links)
- Gauss-Hermite quadratures for functions from Hilbert spaces with Gaussian reproducing kernels (Q438718) (← links)
- Bayesian multi-instance multi-label learning using Gaussian process prior (Q439048) (← links)
- Optimal designs for Gaussian process models via spectral decomposition (Q460654) (← links)
- Statistical inference of regulatory networks for circadian regulation (Q461673) (← links)
- Properties of the posterior distribution of a regression model based on Gaussian random fields (Q462083) (← links)
- Kernel methods in system identification, machine learning and function estimation: a survey (Q462325) (← links)
- Metamodelling with independent and dependent inputs (Q463030) (← links)
- Space-filling Latin hypercube designs based on randomization restrictions in factorial experiments (Q467037) (← links)
- Multiple instance learning via Gaussian processes (Q468681) (← links)
- On the condition number anomaly of Gaussian correlation matrices (Q472459) (← links)
- Whittle-Matérn priors for Bayesian statistical inversion with applications in electrical impedance tomography (Q479868) (← links)
- Fast calculation of multiobjective probability of improvement and expected improvement criteria for Pareto optimization (Q480834) (← links)
- The extended skew Gaussian process for regression (Q483499) (← links)
- Algorithm runtime prediction: methods \& evaluation (Q490455) (← links)
- Bayesian nonparametric estimation of Milky Way parameters using matrix-variate data, in a new Gaussian process based method (Q491403) (← links)
- Multiscale modeling of failure in composites under model parameter uncertainty (Q498537) (← links)
- Query efficient posterior estimation in scientific experiments via Bayesian active learning (Q502395) (← links)
- Sparse plus low rank network identification: a nonparametric approach (Q503197) (← links)
- A Bayesian approach to constrained single- and multi-objective optimization (Q506449) (← links)
- Stationary Gaussian Markov processes as limits of stationary autoregressive time series (Q512009) (← links)
- Fast approximate Bayesian computation for estimating parameters in differential equations (Q517372) (← links)
- Data-driven approximate value iteration with optimality error bound analysis (Q518293) (← links)
- Gradient free active subspace construction using Morris screening elementary effects (Q521467) (← links)
- Nonparametric estimation of an instrumental regression: a quasi-Bayesian approach based on regularized posterior (Q528060) (← links)
- Variable selection and functional form uncertainty in cross-country growth regressions (Q528109) (← links)
- Evolutionary sampling: a novel way of machine learning within a probabilistic framework (Q528711) (← links)
- A belief function theory based approach to combining different representation of uncertainty in prognostics (Q528771) (← links)
- Bounded approximate decentralised coordination via the max-sum algorithm (Q543622) (← links)
- Spiked Dirichlet process priors for Gaussian process models (Q544464) (← links)
- Fixed-domain asymptotics of the maximum likelihood estimator and the Gaussian process approach for deterministic models (Q545143) (← links)
- On information plus noise kernel random matrices (Q605943) (← links)
- Optimization of the angle of attack of delta-winglet vortex generators in a plate-fin-and-tube heat exchanger (Q609917) (← links)
- Extracting optimal datasets for metamodelling and perspectives for incremental samplings (Q622200) (← links)
- Asymptotic behavior of the likelihood function of covariance matrices of spatial Gaussian processes (Q624764) (← links)
- Prediction error identification of linear systems: a nonparametric Gaussian regression approach (Q627072) (← links)
- Gaussian process emulation for second-order Monte Carlo simulations (Q629122) (← links)
- Variable selection for nonparametric Gaussian process priors: Models and computational strategies (Q635421) (← links)
- Gaussian process classification: Singly versus doubly stochastic models, and new computational schemes (Q637979) (← links)
- Classification and categorical inputs with treed Gaussian process models (Q649163) (← links)
- Investigation of optimal position of a vortex generator in a blocked channel for heat transfer enhancement of electronic chips (Q650566) (← links)
- Estimating parameters in stochastic systems: A variational Bayesian approach (Q654174) (← links)
- Supervised neighborhood graph construction for semi-supervised classification (Q663360) (← links)
- Overlapping mixtures of Gaussian processes for the data association problem (Q663366) (← links)
- A semiparametric Bernstein-von Mises theorem for Gaussian process priors (Q664347) (← links)
