Geometric Deep Learning On Groups

Deep learning on groups is an area of geometric deep learning that is rapidly growing. Groups include homogenous spaces with global symmetries, such as the sphere. Practical applications of this technology are prevalent, particularly for the sphere, and are used in a myriad of applications. However, no single approach provides both the desirable properties of equivariance and computational efficiency. We point towards future techniques that could achieve the best of both worlds.