1 citations · 3 across the 3 of their papers we have counts for
6 papers
A Hierarchical Bayesian Model for Stochastic Spatiotemporal SIR Modeling and Prediction of COVID-19 Cases and Hospitalizations
Curtis B. Storlie, Ricardo L. Rojas, Gabriel O. Demuth +18
Most COVID-19 predictive modeling efforts use statistical or mathematical models to predict national- and state-level COVID-19 cases or deaths in the future. These approaches assum…
Bayesian Calibration of Computer Models with Informative Failures
Peter W. Marcy, Curtis B. Storlie
There are many practical difficulties in the calibration of computer models to experimental data. One such complication is the fact that certain combinations of the calibration inp…
Modeling Material Stress Using Integrated Gaussian Markov Random Fields
Peter W. Marcy, Scott A. Vander Wiel, Curtis B. Storlie +2
The equations of a physical constitutive model for material stress within tantalum grains were solved numerically using a tetrahedrally meshed volume. The resulting output included…
Sequential Optimization in Locally Important Dimensions
Munir A. Winkel, Jonathan W. Stallings, Curt B. Storlie +1
Optimizing an expensive, black-box function is challenging when its input space is high-dimensional. Sequential design frameworks first model with a surrogate…
A Bayesian Approach to Multi-State Hidden Markov Models: Application to Dementia Progression
Jonathan P Williams, Curtis B Storlie, Terry M Therneau +2
People are living longer than ever before, and with this arises new complications and challenges for humanity. Among the most pressing of these challenges is of understanding the r…
Prediction of Individual Outcomes for Asthma Sufferers
Curtis B Storlie, Megan E Branda, Michael R Gionfriddo +2
We consider the problem of individual-specific medication level recommendation (initiation, removal, increase, or decrease) for asthma sufferers. Asthma is one of the most common c…