Implicit Neural Representations for Variational Problems on Graphons
We propose a neural exploratory framework for variational problems over graphons, i.e., symmetric measurable functions $[0,1]^2 \to [0,1]$, that arise as limits of dense graph sequences. Such problems are central to two parts of the mathematical literature: extremal graph theory, which studies graph parameter optimisat...
Taeyoung Kim, Jineon Baek, Joonkyung Lee et al.
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