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stat.ML2026
Derivative Gaussian Processes on a Two-Direction Budget
Hyunseok Seung, Matthias Katzfuss
Gradient observations promise more accurate Gaussian process (GP) surrogates, but the cost of incorporating them has long stood in the way of realizing that promise. We propose a d…
stat.ML2026
Scalable Derivative Gaussian Processes via Exact Gradient Reduction
Hyunseok Seung, Matthias Katzfuss
Gradient observations can substantially improve Gaussian process (GP) surrogates, particularly in high-dimensional settings where function evaluations are expensive. However, exact…