surrogate-modeling

Bayesian Compressive Sensing and Dimensionality Reduction for High-Dimensional Models

Talk

Uncertainty Quantification in High-Dimensional, Nonlinear and Expensive Models

Talk

High-dimensional Polynomial Chaos Basis Selection with Bayesian Compressive Sensing

Talk

Sparse Surrogate Model Construction via Compressive Sensing for High-Dimensional Complex Models

Talk

High-dimensional Polynomial Chaos Basis Selection with Bayesian Compressive Sensing

Talk

Surrogate Construction via Bayesian Compressive Sensing for the Community Land Model

Talk

Surrogate-Based Uncertainty Quantification in Climate Models in presence of High Dimensional, Dependent Inputs and Nonsmooth Outputs

Poster

Adaptive Basis Selection and Dimensionality Reduction with Bayesian Compressive Sensing

Talk

Uncertainty Quantification given Discontinuous Model Response and a Limited Number of Model Runs

We outline a methodology for forward uncertainty quantification in systems with uncertain parameters, discontinuous model response, and a limited number of model runs. Our approach involves two stages. First we detect the discontinuity with Bayesian …

Uncertainty Quantification in Climate Modeling

Poster