Research map / Probabilistic and scientific modeling / Molecules and proteins
Learning to Infer Structures of Network Games
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| learn the action-to-network mapping with NuGgeT rather than the strongest reported baseline | network structure inference · Indian Villages | ROC AUC: 0.5823±0.0152 -> 0.6324±0.0167 | Helped |
| learn the action-to-network mapping with NuGgeT rather than the strongest reported baseline | network structure inference · Yelp Ratings | ROC AUC: 0.6796±0.0033 -> 0.7057±0.0035 | Helped |
| add Gaussian noise with std 0.10 to observed actions (ablation) | NuGgeT · BA graphs, linear quadratic, linear influence, and BH games | test accuracy: 99.87±0.02 -> 99.33±0.10 | Hurt |
| add Gaussian noise with std 0.20 to observed actions (ablation) | NuGgeT · BA graphs, linear quadratic, linear influence, and BH games | test accuracy: 99.87±0.02 -> 95.50±0.38 | Hurt |
| increase the number of observed games (ablation) | NuGgeT and compared methods · synthetic network games | performance | Helped |
| increase the number of nodes in each graph (ablation) | NuGgeT and compared methods · synthetic network games | performance | Hurt |
| increase the number of training graphs (ablation) | NuGgeT · synthetic network games | performance | Helped |
| weight binary cross-entropy by the proportion of graph edges (ablation) | NuGgeT training loss · network structure inference | performance | No clear effect |
Closest papers by meaning
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