AI RESEARCH

HOG-Diff: Higher-Order Guided Diffusion for Graph Generation

arXiv CS.AI

ArXi:2502.04308v3 Announce Type: replace-cross Graph generation is a critical yet challenging task, as empirical analyses require a deep understanding of complex, non-Euclidean structures. Diffusion models have recently made significant advances in graph generation, but these models are typically adapted from image generation frameworks and overlook inherent higher-order topology, limiting their ability to capture graph topology.