polynomial-chaos

Fighting the Curse of Dimensionality in Uncertainty Quantification

Talk

PyTUQ - UQ Tools and Workflows for Computational Models

Talk

PyTUQ - Python Toolkit for Uncertainty Quantification

Talk

Uncertainty Quantification in Computational Science -- from Physical Models to Neural Networks

Talk

Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty

Engineering and applied science rely on computational experiments to rigorously study physical systems. The mathematical models used to probe these systems are highly complex, and sampling-intensive studies often require prohibitively many …

Polynomial Chaos Surrogate Construction for Stochastic Models with Parametric Uncertainty

Engineering and applied science relies on computational experiments to rigorously study physical systems. The mathematical models used to probe these systems are highly complex, and sampling-intensive studies often require prohibitively many …

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

This study proposes and assesses a methodology to obtain high-quality probabilistic predictions and uncertainty information of near-landfall tropical cyclone–driven (TC-driven) storm tide and inundation with limited time and resources. Forecasts of …

Global Sensitivity Analysis of a Coupled Multiphysics Model to Predict Surface Evolution in Fusion Plasma--Surface Interactions

We construct a global sensitivity analysis framework for a coupled multiphysics model used to predict the changes in material properties and surface morphology of helium plasma-facing components in future fusion reactors. The model combines the …

Hit Twice by the Curse of Dimensionality; Spatio-Temporal Land Model Calibration using Karhunen-Loeve and Sparse Polynomial Chaos Expansions

Poster

Probabilistic Methods for Forward and Inverse Uncertainty Quantification

Talk