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Equivariant Quantum Graph Circuits

ICML 2022 · Graph learning › GNN architectures · approach: Substructure-aware GNN expressivity · 7 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the single-qubit EDU-QGC circuit with a parameterized CZ edge layer and Hadamard node layerEDU-QGC · 1-WL-indistinguishable graph pairaccuracy: 50% -> 0.625Helped
Increase the number of alternating node and edge layersEDU-QGC · Synthetic cycle graphs (8-cycle evaluation)one-sample accuracyHelped
Increase the number of alternating node and edge layersEDU-QGC · Synthetic cycle graphsoptimization stabilityNo clear effect

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