Daniel G. Ritchie

Diffusion Autoencoders for Sparse Graph Data Compression

A graph-native generative compression framework that conditions a graph denoising diffusion probabilistic model (DDPM) decoder on latent representations of continuous graph-structured signals and shows that the resulting encoded representations are higher-fidelity and more distributionally aligned than those of vanilla...