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NeurIPS 2026U Fribourg, MILAU FribourgTechnische Universität MünchenUniversité de Montréal; MilaU BergenGraph neural networks

No Triangulation Without Representation: Generalization in Topological Deep Learning

Extending a manifold triangulation benchmark reveals GNNs and HOMP can saturate it with proper representations, yet existing models fail to generalize beyond combinatorial structure.

Johannes S. Schmidt, Martin Carrasco, Ernst Röell, Guy Wolf and 2 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI panel: 13 of 20 reviewers recommend it
lenient 3/5
medium 8/10
strict 2/5
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NeurIPS 2026Helmholtz Munich, TU MunichU FribourgUniversité de Montréal; MilaAIDOS Lab, Department of ComputeGraph neural networks

Diversity Curves for Graph Representation Learning

Diversity curves track structural spread across graph coarsening levels to yield interpretable, size-invariant graph embeddings for clustering, visualization, and comparison.

Katharina Limbeck, Nadja Häusermann, Martin Carrasco, Guy Wolf and 1 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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AI panel: 8 of 20 reviewers recommend it
lenient 5/5
medium 3/10
strict 0/5