Pages that link to "Item:Q6162876"
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The following pages link to A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms (Q6162876):
Displaying 5 items.
- A Bayesian mixed shrinkage prior procedure for spatial-stochastic basis selection and evaluation of gPC expansions: applications to elliptic SPDEs (Q729029) (← links)
- Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark (Q6074252) (← links)
- Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy (Q6185714) (← links)
- The deep arbitrary polynomial chaos neural network or how deep artificial neural networks could benefit from data-driven homogeneous chaos theory (Q6488834) (← links)
- A new modified WINDMI jerk system with exponential and sinusoidal nonlinearities, its bifurcation analysis, multistability, circuit simulation and synchronization design (Q6547470) (← links)
