# Can one hear the position of nodes?

arXiv: https://arxiv.org/abs/2211.06325 · HTML: https://mlsanity.com/paper/2211.06325/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 36 references that are in the map.
- First posted on arXiv 10 Nov 2022.

## Builds on (most cited first, 10 of 10)

- [Fast Differentiable Sorting and Ranking](https://mlsanity.com/paper/2002.08871/) (2020)
- [Cooperative Game Theory Approaches for Network Partitioning](https://mlsanity.com/paper/1707.03587/) (2017)
- [Very Deep Convolutional Neural Networks for Raw Waveforms](https://mlsanity.com/paper/1610.00087/) (2016)
- [NetLSD: Hearing the Shape of a Graph](https://mlsanity.com/paper/1805.10712/) (2018)
- [A Comparative Study on End-to-end Speech to Text Translation](https://mlsanity.com/paper/1911.08870/) (2019)
- [vGraph: A Generative Model for Joint Community Detection and Node Representation Learning](https://mlsanity.com/paper/1906.07159/) (2019)
- [Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach](https://mlsanity.com/paper/1905.10418/) (2019)
- [Machine Learning in Network Centrality Measures: Tutorial and Outlook](https://mlsanity.com/paper/1810.11760/) (2018)
- [RiWalk: Fast Structural Node Embedding via Role Identification](https://mlsanity.com/paper/1910.06541/) (2019)
- [Approximating Network Centrality Measures Using Node Embedding and Machine Learning](https://mlsanity.com/paper/2006.16392/) (2020)

## Abstract (arXiv)

Wave propagation through nodes and links of a network forms the basis of spectral graph theory. Nevertheless, the sound emitted by nodes within the resonating chamber formed by a network are not well studied. The sound emitted by vibrations of individual nodes reflects the structure of the overall network topology but also the location of the node within the network. In this article, a sound recognition neural network is trained to infer centrality measures from the nodes' wave-forms. In addition to advancing network representation learning, sounds emitted by nodes are plausible in most cases. Auralization of the network topology may open new directions in arts, competing with network visualization.