Wecanseethis as the slope of the update function changes (middle row of Figure 1), these green lines correspond tothelocations givenbythearrowsinthetoprow.

Learning object-centric representations of complex scenes is a promising step towards enabling efficient abstract reasoning from low-levelperceptual features. Yet, most deep learning approaches learn distributed representations that do not capture the compositional properties of natural scenes.

We represent a higher-order logic formula as a graph that is invariant to variable renaming but still fully preserves syntactic and semantic information.

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