MST-Direct at Scale: Multivariate and Conditional Geostatistical Simulation via Sinkhorn Optimal Transport
Researchers have developed MST-Direct at Scale, an advancement in multivariate geostatistical simulation using optimal transport. This new method extends previous work to handle larger grids and multiple variables, while also incorporating conditional data. The approach uses a sparse Sinkhorn matcher for scalability and a Gaussian backbone to reproduce specified variograms, exactly preserving the multivariate joint distribution and honouring hard data. AI
IMPACT Enhances simulation capabilities for complex spatial data, potentially impacting fields like resource exploration and environmental modeling.