A Hacker’s Guide to Equivariance Geometric deep learning is a field that has picked up considerable momentum recently. And with good reason, as it deals with ways on how to reason over objects (like graphs, meshes, and protein structures) that are tied to impactful tasks downstream (like predicting molecular properties and automating animation). Additionally, it’s setting up a framework that tries to retroactively explain many of the successes of deep learning with the hope of extrapolati...
