Autoregressive Diffusion Model for Graph Generation

Diffusion-based graph generative models have recently obtained promising results for graph generation. However, existing diffusion-based graph generative models are mostly one-shot generative models that apply Gaussian diffusion in the de-quantized adjacency matrix space.

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Cite this as

Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang (2024). Dataset: Autoregressive Diffusion Model for Graph Generation. https://doi.org/10.57702/sagoagon

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2307.08849
Author Lingkai Kong
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Jiaming Cui
Haotian Sun
Yuchen Zhuang
B. Aditya Prakash
Chao Zhang