AI RESEARCH
MAGPI: Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data
arXiv CS.LG
•
ArXi:2603.22050v1 Announce Type: cross Supervised machine learning describes the practice of fitting a parameterized model to labeled input-output data. Supervised machine learning methods have nstrated promise in learning efficient surrogate models that can (partially) replace expensive high-fidelity models, making many-query analyses, such as optimization, uncertainty quantification, and inference, tractable. However, when