collaborators

5 papers

stat.AP2026

Locally stationary Argo ocean heat content estimates: Modeling, validation and uncertainty quantification

Thea Sukianto, Mikael Kuusela, Donata Giglio +3

Argo profiling floats measure seawater temperature and salinity in the upper 2000 meters of the ocean. These floats are uniquely capable of measuring the global Ocean Heat Content…

stat.ME2026

Rapid Approximation Prediction for Kriging

Ziyu Li, Gregory Fasshauer, Douglas Nychka

Exact Kriging and conditional simulation (CS) for uncertainty quantification are computationally infeasible for modern spatial analyses with large numbers of observations and dense…

stat.AP2026

A Non-stationary, Amortized, Transfer Learning Approach for Modeling Italian Air Quality

Alessandro Fusta Moro, Antony Sikorski, Daniel McKenzie +2

Air quality monitoring in Italy relies on sparse, irregular, ground-based stations that provide high-quality but incomplete measurements of pollution. Chemical transport models (CT…

stat.ME2024

Hybrid Bayesian Smoothing on Surfaces

Matthew Hofkes, Douglas Nychka

Modeling spatial processes that exhibit both smooth and rough features poses a significant challenge. This is especially true in fields where complex physical variables are observe…

stat.ME2024

Hybrid Smoothing for Anomaly Detection in Time Series

Matthew Hofkes, Douglas Nychka, Tzahi Cath +2

Many industrial and engineering processes monitored as times series have smooth trends that indicate normal behavior and occasionally anomalous patterns that can indicate a problem…