Tree
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Graph Generation | Tree | A.Ratio850.7 | 36 | |
| Graph property detection | Tree Huge synthetic (test) | F1 Score95 | 17 | |
| Graph property detection | Tree Large synthetic (test) | F1 Score97 | 17 | |
| Graph property detection | Tree Small synthetic (test) | F1 Score98 | 17 | |
| Unsupervised Ensemble Learning | Tree3k | Accuracy95.67 | 13 | |
| Latent Hierarchical Causal Structure Discovery | Tree Uniform noise | Performance Score89 | 12 | |
| Plain graph generation | Tree Dataset | Validity100 | 11 | |
| General Graph Generation | Tree (test) | V.U.N.100 | 7 | |
| Interventional Time Series Forecasting | Tree NLNA (test) | RMSE0.62 | 7 | |
| Observational Time Series Forecasting | Tree NLNA (test) | RMSE0.59 | 7 | |
| Interventional Time Series Forecasting | Tree Additive (test) | RMSE0.54 | 7 | |
| Observational Time Series Forecasting | Tree Additive (test) | RMSE0.57 | 7 | |
| Plain Graph Generation | Tree | V.U.N.84.5 | 6 | |
| Clustering | Tree | Homogeneity78.4 | 5 | |
| Distance matrix comparison | Tree (test) | Pearson Correlation0.822 | 4 | |
| Probabilistic Time-series Forecasting | Tree Synthetic (test) | CRPS (Additive, Obs.)0.19 | 3 | |
| Counterfactual Time Series Forecasting | Tree NLNA (test) | RMSE0.14 | 1 | |
| Counterfactual Time Series Forecasting | Tree Additive (test) | RMSE0.11 | 1 |
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