3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2025
The Sensitivity of Variational Bayesian Neural Network Performance to Hyperparameters
Scott Koermer, Natalie Klein
In scientific applications, predictive modeling is often of limited use without accurate uncertainty quantification (UQ) to indicate when a model may be extrapolating or when more…
physics.geo-ph2024
Bayesian Event Categorization Matrix Approach for Explosion Monitoring
Scott Koermer, Joshua D. Carmichael, Brian J. Williams
Current efforts to correctly categorize natural events from suspected explosion sources with data that is collected by ground- or space-based sensors presents historical challenges…
stat.ME2023★ 3 cited
Augmenting a simulation campaign for hybrid computer model and field data experiments
Scott Koermer, Justin Loda, Aaron Noble +1
The Kennedy and O'Hagan (KOH) calibration framework uses coupled Gaussian processes (GPs) to meta-model an expensive simulator (first GP), tune its ``knobs" (calibration inputs) to…