Author

A. van Beek

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Preprint Aug 2026

Posterior Geometry and Identifiability in Multi-Response Bayesian Calibration

Calibration under model misspecification is inherently ill-posed because calibration parameters and structural discrepancy are statistically confounded without additional assumptions. Bayesian formulations address this ambiguity through prior and covariance modeling choices, including multi-response observations and cr...

A. van Beek, Adam M. Boyce, W. Dawson et al. · 0 citations

#machine learning Preprint Aug 2026

Learning the Geometry of Admissible Hypotheses through Inductive Bias in Training Distributions

This work presents a framework for learning continuous latent representations of admissible partial differential equations by embedding a scientific inductive bias directly into the training distribution, and shows that embedding a scientific inductive bias in the training distribution enables the learning of compact a...

J. Crowley, Faez Ahmed, A. van Beek · 0 citations