Including Partial Differential Equations in Your PyMC3 Model by Ivan Yashchuk

Events PyMCon2020
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Talk Abstract

This tutorial will demonstrate use of PyMC3 for PDE-based inverse problems. We will infer parameters of a simple continuum mechanics model but the demonstrated tools can be readily applied to other complex PDE-based models.

Talk

Ivan Yashchuk

Ivan Yashchuk has 3 years’ experience in computational mechanics and scientific computing with occasional contributions to OSS projects. He received his M.Sc. in Computational Mechanics from Aalto University, Finland and is currently doing PhD research in Probabilistic Machine Learning group at Aalto.

This is a PyMCon 2020 talk

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1 Like
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Thanks @ivan! Not sure if you have talk to @aseyboldt our goto guy for ODE/PDE - there is also https://github.com/aseyboldt/sunode he’s currently working on.

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Yes, I’m aware of his work. Great stuff! It should be even possible to combine FEniCS and sunode for solving time-dependent PDEs.

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Here is the link to the static (non-interactive) version of the tutorial: https://ivanyashchuk.github.io/fenics_pymccon2020/

You can also access the materials with Binder
Binder

Link to the GitHub repo:

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