4 papers
Amortized Bayesian Disease Mapping and Boundary Detection on Heterogeneous Spatial Graphs
Luca Aiello, Sudipto Banerjee
Spatial disease maps help public-health researchers identify geographic inequalities, but standard Bayesian smoothing can obscure localized disparities when neighboring communities…
Spatial Disease Mapping and Disparity Detection Using Generative AI: An Amortized Bayesian Learning Framework
Luca Aiello, Sudipto Banerjee
We introduce an amortized Bayesian framework for spatial boundary detection that generalizes posterior inference across areal graphs with varying numbers of regions and diverse adj…
Bayesian Inference for Spatially-Temporally Misaligned Data Using Predictive Stacking
Soumyakanti Pan, Sudipto Banerjee
Air pollution remains a major environmental risk factor that is often associated with adverse health outcomes. However, quantifying and evaluating its effects on human health is ch…
Process-based Inference for Spatial Energetics Using Bayesian Predictive Stacking
Tomoya Wakayama, Sudipto Banerjee
Rapid developments in streaming data technologies have enabled real-time monitoring of human activity that can deliver high-resolution data on health variables over trajectories or…