polynomial-chaos

Uncertainty Quantification in the Presence of Limited Climate Model Data with Discontinuities

Uncertainty quantification in climate models is challenged by the sparsity of the available climate data due to the high computational cost of the model runs. Another feature that prevents classical uncertainty analyses from being easily applicable …

Uncertainty Quantification and Data Assimilation - Applications in Chemical Kinetics and Climate Modeling

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Bayesian Inference of Spectral Expansions for Predictability Assessment in Stochastic Reaction Networks

Stochastic reaction networks modeled as jump Markov processes serve as the main mathematical representation of biochemical phenomena in cells, particularly when the relevant molecule count is low, causing deterministic macroscale chemical reaction …

Spectral Representation and Reduced Order Modeling of Stochastic Reaction Networks

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Reduced Order Modeling and Dynamical Analysis in Stochastic Reaction Networks

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Predictability and Reduced Order Modeling in Stochastic Reaction Networks

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