This was part of Bayesian Statistics and Statistical Learning

Efficient Invariant Embeddings for multisets, point sets, and graphs

Nadav Dym, Technion - Israel Institute of Technology

Wednesday, December 13, 2023


In many machine learning tasks, the goal is to learn an unknown function which has some known group symmetries. Equivariant machine learning algorithms exploit this by devising architectures (=function spaces) which have these symmetries by construction. Examples include convolutional neural networks which respect translation symmetries, neural networks for graphs or sets which respect their permutation symmetries, or neural networks for 3D point sets which additionally respect Euclidean symmetries.