Guest Editorial: Non-Euclidean Machine Learning.

An editorial is presented on addressing the need for bringing together leading efforts in non-Euclidean deep learning across all communities. Topics include Convolutional Neural Networks (CNNs) relying on classical signal processing models limiting the applicability to data with underlying Euclidean grid-like structure; and multiple levels of abstraction being introduced similarly to multi-layer networks.