6 papers
The Fidelity and Feedback Traps: The Case for Health Digital Twins as Modular Evolving Causal Systems
Nikki L. B. Freeman, Yating Zou, Kyungbok Lee +3
Digital twins for health may be used to compare treatments, project patient trajectories, and support clinical decisions. While related to mechanical digital twins, those initially…
Hierarchical Probabilistic Principal Component Analysis of Longitudinal Data
Xinyu Zhang, Ameer Qaqish, D. Y. Lin +1
In many longitudinal studies, a large number of variables are measured repeatedly over time, with substantial missing data. Existing methods, such as probabilistic principal compon…
On Statistical Inference for Rates of Change in Spatial Processes over Riemannian Manifolds
Didong Li, Aritra Halder, Sudipto Banerjee
Statistical inference for spatial processes from partially realized or scattered data has seen voluminous developments in diverse areas ranging from environmental sciences to busin…
Bayesian Spatiotemporal Wombling
Aritra Halder, Didong Li, Sudipto Banerjee
Stochastic process models for spatiotemporal data underlying random fields find substantial utility in a range of scientific disciplines. Subsequent to predictive inference on the…
Contrastive linear regression
Boyang Zhang, Sarah Nyquist, Andrew Jones +2
Contrastive dimension reduction methods have been developed for case-control study data to identify variation that is enriched in the foreground (case) data X relative to the backg…
Kernel Density Bayesian Inverse Reinforcement Learning
Aishwarya Mandyam, Didong Li, Jiayu Yao +3
Inverse reinforcement learning (IRL) methods infer an agent's reward function using demonstrations of expert behavior. A Bayesian IRL approach models a distribution over candidate…