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Optimal transport distances for directed, weighted graphs: a case study with cell-cell communication networks

arXiv 2309.07030 ↗First posted 13 Sep 2023cs.LG cs.SI cs.SYcited by 0

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Abstract (arXiv)

Comparing graphs by means of optimal transport has recently gained significant attention, as the distances induced by optimal transport provide both a principled metric between graphs as well as an interpretable description of the associated changes between graphs in terms of a transport plan. As the lack of symmetry introduces challenges in the typically considered formulations, optimal transport distances for graphs have mostly been developed for undirected graphs. Here, we propose two distance measures to compare directed graphs based on variants of optimal transport: (i) an earth movers distance (Wasserstein) and (ii) a Gromov-Wasserstein (GW) distance. We evaluate these two distances and discuss their relative performance for both simulated graph data and real-world directed cell-cell communication graphs, inferred from single-cell RNA-seq data.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 21 references that are in the map. First posted on arXiv 13 Sep 2023.

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References · 7

  1. 2019Gromov-Wasserstein Learning for Graph Matching and Node Embeddingcited by 125
  2. 2019GOT: An Optimal Transport framework for Graph comparisoncited by 64
  3. 2014PageRank beyond the Webcited by 51
  4. 2013A New Notion of Effective Resistance for Directed Graphs-Part I: Definition and Propertiescited by 4
  5. 2013A New Notion of Effective Resistance for Directed Graphs-Part II: Computing Resistancescited by 3
  6. 2020A metric on directed graphs and Markov chains based on hitting probabilitiescited by 3
  7. 2022Comparing directed networks via denoising graphlet distributionscited by 2

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