Pages that link to "Item:Q5157268"
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The following pages link to Adaptive Gaussian Process Approximation for Bayesian Inference with Expensive Likelihood Functions (Q5157268):
Displaying 19 items.
- Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming (Q91882) (← links)
- Query efficient posterior estimation in scientific experiments via Bayesian active learning (Q502395) (← links)
- Adaptive sampling-based quadrature rules for efficient Bayesian prediction (Q782004) (← links)
- Efficient optimization of the likelihood function in Gaussian process modelling (Q1623425) (← links)
- Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations (Q2057377) (← links)
- Locally induced Gaussian processes for large-scale simulation experiments (Q2058747) (← links)
- Clustered active-subspace based local Gaussian process emulator for high-dimensional and complex computer models (Q2134712) (← links)
- Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priors (Q2195831) (← links)
- An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems (Q2222423) (← links)
- Iterative construction of Gaussian process surrogate models for Bayesian inference (Q2301102) (← links)
- Bayesian inference using Gaussian process surrogates in cancer modeling (Q2674119) (← links)
- Inferring the unknown parameters in differential equation by Gaussian process regression with constraint (Q2675742) (← links)
- Reprint of: Bayesian inference using Gaussian process surrogates in cancer modeling (Q2679339) (← links)
- A strategy for Bayesian inference for computationally expensive models with application to the estimation of stem cell properties (Q2846453) (← links)
- Adaptive Hessian-Based Nonstationary Gaussian Process Response Surface Method for Probability Density Approximation with Application to Bayesian Solution of Large-Scale Inverse Problems (Q4908642) (← links)
- Adaptive Design and Analysis Via Partitioning Trees for Emulation of a Complex Computer Code (Q5057264) (← links)
- Adaptive multiple importance sampling for Gaussian processes (Q5106877) (← links)
- Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications (Q6052371) (← links)
- Solving Bayesian inverse problems with expensive likelihoods using constrained Gaussian processes and active learning (Q6594408) (← links)
