AgraSSt: approximate graph Stein statistics for interpretable assessment of implicit graph generators
We propose and analyse a novel statistical procedure, coined AgraSSt, to assess the quality of graph generators which may not be available in explicit forms. In particular, AgraSSt can be used to determine whether a learned graph generating process is capable of generating graphs which resemble a gi...
| Main Authors: | , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Curran Associates
2023
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