mlsanityData to 7 Oct 2026

Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics

arXiv 2409.09469 ↗First posted 14 Sep 2024stat.ML cs.LG eess.SPcited by 4

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Abstract (arXiv)

In many data-driven applications, higher-order relationships among multiple objects are essential in capturing complex interactions. Hypergraphs, which generalize graphs by allowing edges to connect any number of nodes, provide a flexible and powerful framework for modeling such higher-order relationships. In this work, we introduce hypergraph diffusion wavelets and describe their favorable spectral and spatial properties. We demonstrate their utility for biomedical discovery in spatially resolved transcriptomics by applying the method to represent disease-relevant cellular niches for Alzheimer's disease.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 11 of its 41 references that are in the map. First posted on arXiv 14 Sep 2024.

Builds on

11 of 41 references.

References · 11

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  2. 2017Graph Attention Networkscited by 8,854
  3. 2017Inductive Representation Learning on Large Graphscited by 6,284
  4. 2016node2vec: Scalable Feature Learning for Networkscited by 1,913
  5. 2014DeepWalk: Online Learning of Social Representationscited by 1,543
  6. 2018Hypergraph Neural Networkscited by 482
  7. 2022The Vendi Score: A Diversity Evaluation Metric for Machine Learningcited by 299
  8. 2019Hypergraph Convolution and Hypergraph Attentioncited by 226
  9. 2019Introducing Hypergraph Signal Processing: Theoretical Foundation and Practical Applicationscited by 20
  10. 2023Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropycited by 13
  11. 2022Learnable Filters for Geometric Scattering Modulescited by 9

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Cited by year

Citing papers per year: 2024: 1; 2025: 3.

4 papers.

  1. 2024Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifoldscited by 13
  2. 2025VDW-GNNs: Vector diffusion wavelets for geometric graph neural networkscited by 1
  3. 2025InfoGain Wavelets: Furthering the Design of Graph Diffusion Waveletscited by 0
  4. 2025STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamicscited by 0