1 citations · 1 across the 5 of their papers we have counts for
5 papers
Characterizing climate pathways using feature importance on echo state networks
Katherine Goode, Daniel Ries, Kellie McClernon
The 2022 National Defense Strategy of the United States listed climate change as a serious threat to national security. Climate intervention methods, such as stratospheric aerosol…
Target Detection on Hyperspectral Images Using MCMC and VI Trained Bayesian Neural Networks
Daniel Ries, Jason Adams, Joshua Zollweg
Neural networks (NN) have become almost ubiquitous with image classification, but in their standard form produce point estimates, with no measure of confidence. Bayesian neural net…
Comparing the quality of neural network uncertainty estimates for classification problems
Daniel Ries, Joshua Michalenko, Tyler Ganter +2
Traditional deep learning (DL) models are powerful classifiers, but many approaches do not provide uncertainties for their estimates. Uncertainty quantification (UQ) methods for DL…
Assessing adult physical activity and compliance with 2008 CDC guidelines using a Bayesian two-part measurement error model
Daniel Ries, Alicia Carriquiry
While there is wide agreement that physical activity is an important component of a healthy lifestyle, it is unclear how many people adhere to public health recommendations on phys…
The Relationship between Moderate to Vigorous Physical Activity and Metabolic Syndrome: A Bayesian Measurement Error Approach
Daniel Ries, Alicia Carriquiry
Metabolic Syndrome (MetS) is a serious condition that can be an early warning sign of heart disease and Type 2 diabetes. MetS is characterized by having elevated levels of blood pr…