bayesian-inference

Using a Surrogate-Assisted Bayesian Framework to Calibrate the Runoff-Generation Scheme in the Energy Exascale Earth System Model (E3SM) v1

Runoff is a critical component of the terrestrial water cycle, and Earth system models (ESMs) are essential tools to study its spatiotemporal variability. Runoff schemes in ESMs typically include many parameters so that model calibration is necessary …

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

Poster

Active Learning and Uncertainty Quantification for Machine Learning Interatomic Potentials

Talk

Quantifying and Reducing Uncertainty in the E3SM Land Model using Surrogate Modeling

Talk

Statistical Learning and Model Error Estimation

Talk

Probabilistic Methods for Forward and Inverse Uncertainty Quantification

Talk

Characterization of Partially Observed Epidemics through Bayesian Inference: Application to COVID-19

We demonstrate a Bayesian method for the “real-time” characterization and forecasting of partially observed COVID-19 epidemic. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The method is …

Uncertainty Quantification with Model Structural Error

Talk

Embedded Model Error Quantification and Propagation in Physical Models

Talk

Calibration and Propagation of Model Structural Error for E3SM Land Model

Poster