mlsanityData to 14 Oct 2026

Structure from Voltage

arXiv 2203.00063 ↗First posted 28 Feb 2022cs.LG cs.SIcited by 0

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Abstract (arXiv)

Effective resistance (ER) is an attractive way to interrogate the structure of graphs. It is an alternative to computing the eigen-vectors of the graph Laplacian. Graph laplacians are used to find low dimensional structures in high dimensional data. Here too, ER based analysis has advantages over eign-vector based methods. Unfortunately Von Luxburg et al. (2010) show that, when vertices correspond to a sample from a distribution over a metric space, the limit of the ER between distant points converges to a trivial quantity that holds no information about the structure of the graph. We show that by using scaling resistances in a graph with n vertices by n2, one gets a meaningful limit of the voltages and of effective resistances. We also show that by adding a "ground" node to a metric graph one gets a simple and natural way to compute all of the distances from a chosen point to all other points.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 31 references that are in the map. First posted on arXiv 28 Feb 2022.

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7 of 31 references.

References · 7

  1. 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,898
  2. 2021LDLE: Low Distortion Local Eigenmapscited by 11
  3. 2021t-SNE, Forceful Colorings and Mean Field Limitscited by 10
  4. 2018Graph Algorithms for Topology Identification using Power Grid Probingcited by 5
  5. 2013The Impact of the Topology on Cascading Failures in Electric Power Gridscited by 2
  6. 2015A network approach for power grid robustness against cascading failurescited by 1
  7. 2020Phylogenetic networks as circuits with resistance distancecited by 1

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