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Graph Convolutional Attention: A Spectral Perspective on Graph Denoising and Diffusion
Denoising graphs is a fundamental problem in graph learning and the core operation of graph diffusion models. Attention based architectures like graph transformers have recently shown promise in denoising graphs. However, our principled understanding of attention based graph denoising remains limited, making it unclear whether standard attention is the right mechanism for this task. Here we show that, under a deno...