most citedSpatially Varying Deep Functional Neural Network: Application in Large-Scale Crop Yield Prediction

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

stat.AP20261 cited

Spatially Varying Deep Functional Neural Network: Application in Large-Scale Crop Yield Prediction

Yeonjoo Park, Bo Li, Yehua Li

Accurate prediction of crop yield is critical for supporting food security, agricultural planning, and economic decision-making. However, yield forecasting remains a significant ch…

stat.ME2026

Scalable Changepoint Detection for Large Spatiotemporal Data on the Sphere

Samantha Shi-Jun, Bo Li

We propose a novel Bayesian framework for changepoint detection in large-scale spherical spatiotemporal data, with broad applicability in environmental and climate sciences. Our ap…

stat.ME2026

Combining Climate Models using Bayesian Regression Trees and Random Paths

John C. Yannotty, Thomas J. Santner, Bo Li +1

General circulation models (GCMs) are essential tools for climate studies. Such climate models may have varying accuracy across the input domain, but no model is uniformly best. On…

q-bio.QM2025

MAT-MPNN: A Mobility-Aware Transformer-MPNN Model for Dynamic Spatiotemporal Prediction of HIV Diagnoses in California, Florida, and New England

Zhaoxuan Wang, Weichen Kang, Yutian Han +2

Human Immunodeficiency Virus (HIV) has posed a major global health challenge for decades, and forecasting HIV diagnoses continues to be a critical area of research. However, captur…

stat.AP2025

Tracing the impacts of Mount Pinatubo eruption on regional climate using spatially-varying changepoint detection

Samantha Shi-Jun, Lyndsay Shand, Bo Li

Significant events, such as volcanic eruptions, can have global and long-lasting impacts on climate. These global impacts, however, are not uniform across space and time. Understan…