Research map / Graph learning / Graph algorithms and clustering
Residual2Vec: Debiasing graph embedding with random graphs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the soft configuration model as the null graph to remove degree bias | Residual2Vec (r2v-config) · Link prediction on empirical graphs | AUC-ROC | Helped |
| Use the soft configuration model as the null graph to remove degree bias | Residual2Vec (r2v-config) · LFR community detection benchmark | AUC-ROC | Helped |
| Add the baseline offset z_i to the link prediction score | Residual2Vec · Link prediction on empirical graphs | AUC-ROC | Helped |
| Use a degree-preserving, year-grouped dcSBM null model instead of a degree-only configuration null model | Residual2Vec · Web of Science journal citation graph | R^2-score for year dependence | Helped |
| Use a degree-preserving, year-grouped dcSBM null model | Residual2Vec · Web of Science journal citation graph | Impact factor and subject-category prediction | Mixed |
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