most citedStochastic identification of malware with dynamic traces

20 citations · 37 across the 6 of their papers we have counts for

collaborators

6 papers

stat.AP2023

Bayes Watch: Bayesian Change-point Detection for Process Monitoring with Fault Detection

Alexander C. Murph, Curtis B. Storlie, Patrick M. Wilson +2

When a predictive model is in production, it must be monitored in real-time to ensure that its performance does not suffer due to drift or abrupt changes to data. Ideally, this is…

stat.AP2023

A Novel Alternating Joint Longitudinal Model for Post-ICU Hemoglobin Prediction

Gabriel Demuth, Curtis Storlie, Matthew A. Warner +3

Anemia is common in patients post-ICU discharge. However, which patients will develop or recover from anemia remains unclear. Prediction of anemia in this population is complicated…

stat.ME20141 cited

Upscaling Uncertainty with Dynamic Discrepancy for a Multi-scale Carbon Capture System

K. Sham Bhat, David S. Mebane, Curtis B. Storlie +1

Uncertainties from model parameters and model discrepancy from small-scale models impact the accuracy and reliability of predictions of large-scale systems. Inadequate representati…

stat.AP201413 cited

Modeling and Predicting Power Consumption of High Performance Computing Jobs

Curtis Storlie, Joe Sexton, Scott Pakin +3

Power is becoming an increasingly important concern for large supercomputing centers. Due to cost concerns, data centers are becoming increasingly limited in their ability to enhan…

stat.ME20143 cited

Calibration of Computational Models with Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA

Curtis B. Storlie, William A. Lane, Emily M. Ryan +2

It has become commonplace to use complex computer models to predict outcomes in regions where data does not exist. Typically these models need to be calibrated and validated using…

stat.AP201420 cited

Stochastic identification of malware with dynamic traces

Curtis Storlie, Blake Anderson, Scott Vander Wiel +3

A novel approach to malware classification is introduced based on analysis of instruction traces that are collected dynamically from the program in question. The method has been im…