betsymccall.net Lifelong Learning CDSE Thesis (Dissertation) Learning Resources

Emulators are a way to use machine learning methods, like Gaussian Processes, to estimate the runs of modeling results without having to run quite as many large model runs.

Designing accurate emulators for scientific processes using calibration-driven deep models
From models of galaxies to atoms, simple AI shortcuts speed up simulations by billions of times
Self-learning Emulators and Eigenvector Continuation
Machine Learning Emulation of Spatial Deposition from a Multi-Physics Ensemble of Weather and Atmospheric Transport Models
Meta-Modelling and Deploying ML Software (video)
Session Panel: Inferencing, Emulators & Interpretability (video)
Some thoughts on Gaussian processes for emulation of deterministic computer models: Michael Stein (video)

These are a brief introduction to emulation. Also check out my page on partial parallel emulation.

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