National Aeronautics and Space Administration, Jet Propulsion Laboratory, USA
Uncertainty quantification for analysis and global prediction of carbon dioxide using data from the Orbiting Carbon Observatory-2 satellite
Spatial statistical modelling to estimate CO2 in atmospheric columns at any location on the globe, followed by estimation of near-surface fluxes and a statistical analysis of the uncertainties associated with these estimates. Learn more...
University of Missouri, Department of Statistics, USA
Spatio-temporal statistics for US federal agencies, particularly the Census Bureau, and for official statistics surveys
Developing methodological research and applied scientific knowledge for official statistics through the use of hierarchical spatio-temporal statistical modelling. Focus is on the American Community Survey conducted by the US Census Bureau. Learn more...
Academia Sinica, Institute of Statistical Science, Taiwan
Enhanced False Discovery Rate (EFDR) for detecting change
Transforming images to wavelet space and using EFDR to test the presence of signals in background noise. Learn more...
University of Bristol, School of Geographical Sciences, School of Chemistry, and School of Geographical Sciences, UK
Sea-level rise
Assessing the Antarctic contribution to sea-level rise using multivariate spatio-temporal models. Learn more...
The University of Texas at El Paso, Department of Mathematical Sciences, USA
Climate inference for Australian daily rainfall
Using Bayesian hierarchical spatio-temporal mixture models to analyse the climatology of Australian rainfall. Learn more...
Eurecom, Data Science Department, France
Warping for modelling nonstationary spatial covariances
Using deep learning techniques for modeling spatial covariances on warped spaces. Learn more...