mlsanityData to 14 Oct 2026

ICML 2023 Topological Deep Learning Challenge : Design and Results

arXiv 2309.15188 ↗First posted 26 Sep 2023cs.LGcited by 7

Not on the map. Why?

Abstract (arXiv)

This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competition asked participants to provide open-source implementations of topological neural networks from the literature by contributing to the python packages TopoNetX (data processing) and TopoModelX (deep learning). The challenge attracted twenty-eight qualifying submissions in its two-month duration. This paper describes the design of the challenge and summarizes its main findings.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 20 of its 25 references that are in the map. First posted on arXiv 26 Sep 2023.

Builds on

20 of 25 references.

References · 20

  1. 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,434
  2. 2021Weisfeiler and Lehman Go Cellular: CW Networkscited by 218
  3. 2021UniGNN: a Unified Framework for Graph and Hypergraph Neural Networkscited by 130
  4. 2021You are AllSet: A Multiset Function Framework for Hypergraph Neural Networkscited by 127
  5. 2020Simplicial Neural Networkscited by 110
  6. 2020HNHN: Hypergraph Networks with Hyperedge Neuronscited by 109
  7. 2022Topological Deep Learning: Going Beyond Graph Datacited by 97
  8. 2018Random Walks on Simplicial Complexes and the normalized Hodge 1-Laplaciancited by 86
  9. 2021Principled Simplicial Neural Networks for Trajectory Predictioncited by 77
  10. 2020Be More with Less: Hypergraph Attention Networks for Inductive Text Classificationcited by 74
  11. 2020HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphscited by 54
  12. 2023Architectures of Topological Deep Learning: A Survey of Message-Passing Topological Neural Networkscited by 43
8 more
  1. 2022Simplicial Attention Networkscited by 41
  2. 2022Cell Attention Networkscited by 35
  3. 2023Convolutional Learning on Simplicial Complexescited by 27
  4. 2022Simplicial Convolutional Filterscited by 18
  5. 2021Simplicial Complex Representation Learningcited by 17
  6. 2021Dist2Cycle: A Simplicial Neural Network for Homology Localizationcited by 16
  7. 2022Message Passing Neural Networks for Hypergraphscited by 13
  8. 2021Dynamic Hypergraph Convolutional Networks for Skeleton-Based Action Recognitioncited by 9

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 2.

7 papers.

  1. 2024Position: Topological Deep Learning is the New Frontier for Relational Learningcited by 66
  2. 2024TopoX: A Suite of Python Packages for Machine Learning on Topological Domainscited by 22
  3. 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Frameworkcited by 12
  4. 2024ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domaincited by 3
  5. 2025Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passingcited by 2
  6. 2026Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentationcited by 0
  7. 2026Differentiable Lifting for Topological Neural Networkscited by 0