Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks

@article{Baena2021InferringGS,
  title={Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks},
  author={Raphael Baena and Lucas Drumetz and Vincent Gripon},
  journal={2021 29th European Signal Processing Conference (EUSIPCO)},
  year={2021},
  pages={2169-2173}
}
The field of Graph Signal Processing (GSP) has proposed tools to generalize harmonic analysis to complex domains represented through graphs. Among these tools are translations, which are required to define many others. Most works propose to define translations using solely the graph structure (i.e. edges). Such a problem is ill-posed in general as a graph conveys information about neighborhood but not about directions. In this paper, we propose to infer translations as edge-constrained… 

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