E(3) Equivariant Neural Network Tutorial

Current tutorial page click here.

Tutors: Tess E. Smidt and Risi Kondor

A special thanks to IPAM and the organizers of the “Machine Learning for Physics and the Physics of Learning” Long Program for hosting the tutorial, especially Christian Ratsch, Frank Noé and Cecilia Clementi.

Tess would also like to thank Mario Geiger, Ben Miller, Kostiantyn Lapchevskyi for all they do for the se3cnn repo and them, Daniel Murnane, and Sean Lubner for many conversations that lead to the generation of the tutorial notebooks.

Spacetime coordinates

Thursday, November 14, 2019
10:00 am - noon, 1:30 - 2:30 pm
Main Lecture Hall
Institute for Pure and Applied Mathematics (IPAM)
University of California, Los Angeles

10:00 am - noon

Tutorials with lecture and code

1:30 - 2:30 pm

Remaining topics and open discussion

Recommended Reading


For code examples, we will be using the se3cnn repository. Installation instructions can be found here. To test your installation of se3cnn, we recommend running the following code example.

To follow along during the (original) tutorial, we recommend you clone the (original) tutorial repository in addition to installing se3cnn.

git clone git@github.com:blondegeek/e3nn_tutorial.git --branch 0.0

Be sure to unzip the cache.zip which has all Clebsch-Gordon tensors up to L=10 so that you don’t have to compute these locally.

Tutorial notebooks

Why notebook AND html?

For the notebooks that use plotly the notebooks are distributed without cells executed because the plots are large (because Tess made them too high-resolution… oops.). If you download the HTML verison, you can interact with the plots without needing to execute the code.

Got feedback on the code tutorials?

Tess wants to hear all about it, so please, please, please write Tess an email at tsmidt@lbl.gov or blondegeek@gmail.com! The goal is to make these notebooks maximally useful to others.