PARD: Permutation-invariantAutoregressiveDiffusion forGraphGeneration

Neural Information Processing Systems 

Specifically, we show that contrary to sets, elements in a graph are not entirely unordered and there is a unique partial order for nodes and edges. With this partial order,PARD generates a graph in a block-by-block, autoregressivefashion, where each block'sprobability isconditionally modeled by a shared diffusion model with an equivariant network.

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