mlsanityData to 7 Oct 2026

Spatial Graph Convolution Neural Networks for Water Distribution Systems

arXiv 2211.09587 ↗First posted 17 Nov 2022cs.LGcited by 3

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Abstract (arXiv)

We investigate the task of missing value estimation in graphs as given by water distribution systems (WDS) based on sparse signals as a representative machine learning challenge in the domain of critical infrastructure. The underlying graphs have a comparably low node degree and high diameter, while information in the graph is globally relevant, hence graph neural networks face the challenge of long-term dependencies. We propose a specific architecture based on message passing which displays excellent results for a number of benchmark tasks in the WDS domain. Further, we investigate a multi-hop variation, which requires considerably less resources and opens an avenue towards big WDS graphs.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 18 of its 32 references that are in the map. First posted on arXiv 17 Nov 2022.

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18 of 32 references.

References · 18

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6 more
  1. 2018Adaptive Graph Convolutional Neural Networkscited by 155
  2. 2018Large-Scale Learnable Graph Convolutional Networkscited by 113
  3. 2020A Survey on The Expressive Power of Graph Neural Networkscited by 111
  4. 2022Traffic4cast at NeurIPS 2021 -- Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processescited by 15
  5. 2021Reconstructing nodal pressures in water distribution systems with graph neural networkscited by 6
  6. 2022Graph Neural Network and Koopman Models for Learning Networked Dynamics: A Comparative Study on Power Grid Transients Predictioncited by 5

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Cited by year

Citing papers per year: 2023: 1; 2024: 0; 2025: 2.

3 papers.

  1. 2025Exact Computation of Any-Order Shapley Interactions for Graph Neural Networkscited by 12
  2. 2023Graph Neural Networks for Pressure Estimation in Water Distribution Systemscited by 8
  3. 2025Scalable and Robust Physics-Informed Graph Neural Networks for Water Distribution Systemscited by 0