Thenweusethevariantsubgraphs,i.e., complements of invariant subgraphs, to infer the latent environment labels.

In this paper, we show this is not the case by disentangling the notions of expressivity and learnability.

Let x 2 RD beadatapoint.

Here,weproposea spatio-translational embeddingmodel,called BoxE,that simultaneously addresses all these limitations.

We develop a new primitive for stochastic optimization: a low-bias, low-cost estimator of the minimizerx? of any Lipschitz strongly-convex function.