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Gaussian Process Latent Factor Regression for Low-Data, High-Dimensional Output Problems

arXiv cs.LG · 2026-06-08 Cached

Proposes Gaussian process latent factor regression (GPLFR) for low-data, high-dimensional output problems, demonstrating it with a spatially resolved emulator of global climate models for rocky exoplanets.

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