Discrete Diffusion for Large Graph Generation via Structural Candidate Restriction

Synthesizing realistic graphs at scale is vital when the graphs of interest are large and real-world samples are limited or access-sensitive. Diffusion-based generators have recently driven much of the progress, offering high modeling capacity, but most such methods have…

Yassin Mohamadi, Zeno Geradts, Marcel Worring·arXiv — cs.AI

Original Source

Key Takeaways

01.Synthesizing realistic graphs at scale is vital when the graphs of interest are large and real-world samples are limited or access-sensitive
02.Diffusion-based generators have recently driven much of the progress, offering high modeling capacity, but most such methods have…

This material is provided as an extended analytical summary.

Read full article at source

Aggregated within AI Qazaqstan national intelligence stream with author attribution.