arXiv Machine Learning August 20, 2026 By Resul Tugay, Eren Olu\u{g}, Elif Ak, Sule Gunduz Oguducu

GraphK: Variable-Size Graph Generation with Efficient Edge Construction

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GraphK introduces an encoder‑sampler‑decoder framework that generates variable‑size graphs efficiently. It learns permutation‑invariant latent representations and samples new node embeddings via maximum likelihood, enabling both upscaling and downscaling of graph size. Edge construction uses KDTree‑based top‑k neighbor search in latent space, reducing computational cost while capturing graph properties.

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