2 citations · 4 across the 4 of their papers we have counts for
4 papers
How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning
Yuanyuan Wang, Qian Song, Dawood Wasif +4
Uncertainty quantification (UQ) is essential for assessing the reliability of Earth observation (EO) products. However, the extensive use of machine learning models in EO introduce…
Physics-embedded Fourier Neural Network for Partial Differential Equations
Qingsong Xu, Nils Thuerey, Yilei Shi +3
We consider solving complex spatiotemporal dynamical systems governed by partial differential equations (PDEs) using frequency domain-based discrete learning approaches, such as Fo…
Large-scale flood modeling and forecasting with FloodCast
Qingsong Xu, Yilei Shi, Jonathan Bamber +2
Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost. This limits their ability to a…
Spatio-temporal spread of COVID-19 and its associations with socioeconomic, demographic and environmental factors in England: A Bayesian hierarchical spatio-temporal model
Xueqing Yin, John M. Aiken, Richard Harris +1
Exploring the spatio-temporal variations of COVID-19 transmission and its potential determinants could provide a deeper understanding of the dynamics of disease spread. This study…