Positional diffusion: Graph-based diffusion models for set ordering

Francesco Giuliari, Gianluca Scarpellini, Stefano Fiorini, Stuart James, Pietro Morerio, Yiming Wang, Alessio Del Bue

Abstract: Highlights•The article presents a novel method for Ordering Elements of a Set in 1D and 2D space.•We propose a task-agnostic method, Positional Diffusion for different ordering tasks•Our approach combines Graph Neural Networks with Diffusion Probabilistic Models.•Without any task-specific modes, our method can outperform task-specific approaches.•We test our approach on Sentence ordering, Visual Puzzles, and Furniture Arrangement.