Removing explicit noise-level conditioning from graph diffusion models is often harmless, and the paper gives concentration and error-propagation bounds explaining why, with supporting experiments on QM9 and soc-Epinions1.
Difusco: Graph-based diffusion solvers for combinatorial optimization
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Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models
Removing explicit noise-level conditioning from graph diffusion models is often harmless, and the paper gives concentration and error-propagation bounds explaining why, with supporting experiments on QM9 and soc-Epinions1.