Accelerating large-scale simulations with AI.
Replace complex simulations with fast, accurate emulators.
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AutoEmulate is a Python library for automatically
creating accurate and efficient emulators of complex
simulations.
Run a complete machine learning pipeline to compare
and optimise a wide range of models, with functions
for downstream tasks like prediction, sensitivity
analysis and calibration.
Open source & free to use
Low code
Data-processing, model comparison, cross-validation, hyperparameter search and more in few lines of code.
PyTorch first
PyTorch backend makes emulators easy to integrate into downstream applications.
Domain agnostic
Integrate complex simulator models from any domain into the simulator-in-the-loop workflow and leverage active learning.
State of the art emulation
Classical methods
Radial Basis Functions
Polynomial Regression
Machine Learning
Random Forests
Gradient Boosting
Support Vector Machines
Neural Networks
Probabilistic methods
Gaussian Processes
Ensembles
Quick start
Install
pip install autoemulateFind the best emulator in just a few lines of code
ae = AutoEmulate(x, y)
best_result = ae.best_result()
best_emulator = best_result.model