arXiv Machine Learning June 9, 2026 By Tcharlies Bachmann Schmitz

MST-Direct at Scale: Multivariate and Conditional Geostatistical Simulation via Sinkhorn Optimal Transport

Read the original on arXiv Machine Learning →

arXiv:2606. 07578v1 Announce Type: new Abstract: This paper extends MST-Direct, a Matching-via-Sinkhorn-Transport approach for multivariate geostatistical simulation, from the original bivariate, unconditional, small-grid formulation to multivariate, conditional, and large-grid settings.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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