Welcome to surmise’s documentation!

surmise is a Python library for facilitating Bayesian calibration with statistical emulation. surmise’s modular design allows for mix-and-matching emulation and calibration strategies for a specific scientific problem.
To begin using surmise, we encourage checking out the following pages:
Jupyter notebook: Full usage with Gaussian process emulation on Google Colab.
Expected use case examples and scientific examples.
Github project page: surmise is open source and provided under the MIT license.
User Guide:
Usage Examples & Tutorials:
Developer Guide:
Collaborators & Contributors: