This paper introduces and evaluates G2Sphere, a general method for mapping object geometries to spherical signals using equivariant neural networks and the Fourier Transform.

We show that two-stage CATE estimators can be suboptimal for decision-making and propose a novel method to improve them.

Learning a relational policy to solve planning problems by ranking actions using a new graph representation and decoder architecture