4 papers
A new framework for non-stationary spatio-temporal data fusion of multi-fidelity models
Pietro Colombo, Fabio Sigrist, Claire Miller +3
We propose a new scalable framework for spatio-temporal data fusion with multi-fidelity Gaussian processes (MFGPs) that enables fully likelihood-based inference for both stationary…
SCARFACE: a harmonized spatio-temporal dataset integrating socio-economic, environmental, and agricultural indicators for the Po Valley (Italy), 2011--2024
Paolo Maranzano, Pietro Colombo, Felicetta Carillo +5
We present "Sequestering CARbon through Forests, AgriCulture, and land usE (SCARFACE)", a harmonized spatio-temporal dataset that integrates climate, air quality, airborne pollutan…
A Simple and Robust Multi-Fidelity Data Fusion Method for Effective Modeling of Citizen-Science Air Pollution Data
Camilla Andreozzi, Pietro Colombo, Philipp Otto
We propose a robust multi-fidelity Gaussian process for integrating sparse, high-quality reference monitors with dense but noisy citizen-science sensors. The approach replaces the…
Simple yet effective: a comparative study of statistical models for yearly hurricane forecasting
Pietro Colombo, Raffaele Mattera, Philipp Otto
In this paper, we study the problem of forecasting the next year's number of Atlantic hurricanes, which is relevant in many fields of applications such as land-use planning, hazard…