1 citations · 1 across the 3 of their papers we have counts for
3 papers
A Bayesian Hierarchical Model Framework to Quantify Uncertainty of Tropical Cyclone Precipitation Forecasts
Stephen A. Walsh, Marco A. R. Ferreira, Dave Higdon +1
Tropical cyclones present a serious threat to many coastal communities around the world. Many numerical weather prediction models provide deterministic forecasts with limited measu…
Quantification of Uncertainties in Nuclear Density Functional theory
N. Schunck, J. D. McDonnell, D. Higdon +2
Reliable predictions of nuclear properties are needed as much to answer fundamental science questions as in applications such as reactor physics or data evaluation. Nuclear density…
Computer Model Calibration using the Ensemble Kalman Filter
Dave Higdon, Matt Pratola, James Gattiker +6
The ensemble Kalman filter (EnKF) (Evensen, 2009) has proven effective in quantifying uncertainty in a number of challenging dynamic, state estimation, or data assimilation, proble…