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stat.ME2026
Spatially orthogonal factor models for spatial transcriptomics and remote sensing data
Dan Cunha, Lukas M. Weber, Mark A. Friedl +1
Principal component analyses are often applied to spatial data towards inference on latent modes of spatial variation. These analyses are widespread across domains including spatia…
stat.ME2025
Bernstein Polynomial Processes for Continuous Time Change Detection
Dan Cunha, Mark Friedl, Luis Carvalho
There is a lack of methodological results for continuous time change detection due to the challenges of noninformative prior specification and efficient posterior inference in this…