2026
CLM-AI-003631= GIN distinguishing power = 1-WLEXACT VALUEThe cited theorem establishes GIN distinguishing power = 1-WL under the recorded model.Source: How Powerful are Graph Neural Networks? — Graph Isomorphism Network expressivity ↗
PROVENWith injective aggregation and sufficient capacity, GIN matches one-dimensional Weisfeiler-Leman distinguishing power.
The question, scope, and sources behind this Registry record.
Under the recorded graph learning model, establish GIN distinguishing power = 1-WL.
Current frontiers derived from accepted Claims.
The accepted equality closes this optimization result.
Assertions tied to evidence, attribution, and review.
The frontier as it changed over time.
Only accepted Claims matching the current specification contribute to the displayed bounds. Strict inequalities remain open; contradictory Claims require editorial review.
No accepted machine-checked reproductions are recorded for this Limit.
Limits Registry. LR-003631. Graph Isomorphism Network expressivity. 2026.