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GAUSSIAN PROCESS REGRESSION AND CONDITIONAL KARHUNEN-LOÈVE EXPANSION FOR FORWARD UNCERTAINTY QUANTIFICATION AND INVERSE MODELING IN THE PRESENCE OF MEASUREMENT NOISE
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References

  • 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
  • 2005High-Order Collocation Methods for Differential Equations with Random Inputs1,522 cited
  • 2003Modeling uncertainty in flow simulations via generalized polynomial chaos1,428 cited
  • 2008A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data942 cited
  • 2006Stochastic spectral methods for efficient Bayesian solution of inverse problems471 cited
  • 2009An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations447 cited
  • 2014Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies212 cited
  • 2013Reweighted minimization method for stochastic elliptic differential equations108 cited
  • 2012Local and Dimension Adaptive Stochastic Collocation for Uncertainty Quantification41 cited
  • 2020Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models21 cited

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