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Fabian Ruehle

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#graph neural networks Preprint Aug 2026

Learning Topological Features of $\widehat Z$-invariants

This paper initiates a systematic approach to handling mathematical data structured as (truncated) infinite $q-series, or equivalently, infinite series of integers, and demonstrates that neural networks can reliably extract essential topological information, such as homology class and underlying graph structure, direct...

Brandon Robinson, Shimal Harichurn, Fabian Ruehle et al. · 0 citations

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