An Efficient Sampling Method for Regression-Based Polynomial Chaos Expansion
From MaRDI portal
Publication:4588786
DOI10.4208/cicp.020911.200412azbMath1378.62025OpenAlexW2166849702MaRDI QIDQ4588786
François Glineur, Benoît Colson, Samih Zein
Publication date: 27 October 2017
Published in: Communications in Computational Physics (Search for Journal in Brave)
Full work available at URL: https://semanticscholar.org/paper/1be5748a5d4f3781dc960b14c9d2b5c546235ed8
Related Items (9)
Adaptive weighted least-squares polynomial chaos expansion with basis adaptivity and sequential adaptive sampling ⋮ An active sparse polynomial chaos expansion approach based on sequential relevance vector machine ⋮ Towards optimal sampling for learning sparse approximation in high dimensions ⋮ Sequential Design of Experiment for Sparse Polynomial Chaos Expansions ⋮ An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework ⋮ A hybrid sequential sampling strategy for sparse polynomial chaos expansion based on compressive sampling and Bayesian experimental design ⋮ A new non-intrusive polynomial chaos using higher order sensitivities ⋮ Least squares polynomial chaos expansion: a review of sampling strategies ⋮ Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark
This page was built for publication: An Efficient Sampling Method for Regression-Based Polynomial Chaos Expansion
