Protected: A Scalable Algorithm for Generating Non-Uniform Space Filling DesignsSession 3B – A Scalable Algorithm for Generating Non-Uniform Space Filling Designs
Protected: A critique of neutrosophic statistical analysis illustrated with interval data from designed experimentsSession 3B – A critique of neutrosophic statistical analysis illustrated with interval data from designed experiments
Protected: Large Row-Constrained Supersaturated Designs for High-throughput ScreeningSession 3C – Large Row-Constrained Supersaturated Designs for High-throughput Screening
Protected: Optimizing User Experience in Statistical Tools through Experimental DesignSession 3C – Optimizing User Experience in Statistical Tools through Experimental Design
Protected: A Case Study in Image Analysisfor Engine CleanlinessSession 4A – A Case Study in Image Analysis for Engine Cleanliness
Protected: Powerful Foldover DesignsSession 4B – Powerful Foldover Designs
Protected: Exploratory Image Data Analysis for Quality Improvement Hypothesis GenerationSession 5C – Exploratory Image Data Analysis for Quality Improvement Hypothesis Generation
Protected: Boundary Peeling: An Outlier Detection MethodSession 5C – Boundary Peeling: An Outlier Detection Method
Protected: Change Takes Time: Using Input-Varying Weights to Determine a Soft Changepoint in Mixed PopulationsSession 6A – Change Takes Time: Using Input-Varying Weights to Determine a Soft Changepoint in Mixed Populations
Protected: Deep Gaussian processes for estimation of failure probabilities in complex systemsSession 6B – Deep Gaussian processes for estimation of failure probabilities in complex systems
Protected: Dealing with Sample Bias: Alternative Approaches and the Fundamental Questions They RaiseSession 6C: Dealing with Sample Bias: Alternative Approaches and the Fundamental Questions They Raise
Protected: Boundary-constrained Gaussian random fieldsPoster 1 – Boundary-constrained Gaussian random fields
Protected: Optimal Experimental Designs Robust to Missing ObservationsPoster 5 – Optimal Experimental Designs Robust to Missing Observations
