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Philipp Hennig

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#machine learning Preprint Oct 2026

Learn Only Where You Can't Compute: Structured Corrections to Gaussian Process Posteriors

Physics-informed Gaussian processes (GPs) provide a principled framework for scientific inference by expressing uncertainty over empirical measurements, boundary conditions, and governing equations. However, they struggle to scale to larger datasets and nonlinear information. Conversely, diffusion models excel at learn...

Tobias Weber, Carla Sagebiel, Philipp Hennig · 0 citations

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