Including Partial Differential Equations in Your PyMC3 Model by Ivan Yashchuk

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.


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

Learn more about PyMCon!

PyMCon is an asynchronous-first virtual conference for the Bayesian community.

We have posted all the talks here in Discourse on October 24th, one week before the live PyMCon session for everyone to see and discuss at their own pace.

If you are available on October 31st you can register for the live session here!, but if you are not don’t worry, all the talks are already available here on Discourse (keynotes will be posted after the conference) and you can network here on Discourse and on our Zulip.

We value the participation of each member of the PyMC community and want all attendees to have an enjoyable and fulfilling experience. Accordingly, all attendees are expected to show respect and courtesy to other attendees throughout the conference and at all conference events. Everyone taking part in PyMCon activities must abide by the PyMCon Code of Conduct. You can report any incident through this from.

If you want to support PyMCon and the PyMC community but you can’t attend the live session, consider donating to PyMC

Do you have suggestions to improve PyMCon? We have an anonymous suggestion box waiting for you

Have you enjoyed PyMCon? Please fill our PyMCon attendee survey. It is open to both async PyMCon attendees and people taking part in the live session.

1 Like

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

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


Here is the link to the static (non-interactive) version of the tutorial:

You can also access the materials with Binder

Link to the GitHub repo: