is a hallmark of human intelligence. By contrast, the generalization exhibited by
contemporary neural network algorithms is largely limited to interpolation between data
points in their training corpora. In this paper, we consider the challenge of learning
representations that support extrapolation. We introduce a novel visual analogy benchmark
that allows the graded evaluation of extrapolation as a function of distance from the convex …