Barycenter Computation on Location-scatter population (Gaussian P0 = N(0, ID)) (test)
100BW2-UVP[C]
Evaluation results
| Method | Links | |
|---|---|---|
| [C]D=22022.01 | 100 | |
| [C]D=42022.01 | 100 | |
| [C]D=82022.01 | 100 | |
| [C]D=162022.01 | 100 | |
| [C]D=322022.01 | 100 | |
| [C]D=642022.01 | 100 | |
| [C]D=1282022.01 | 100 | |
| [SCW2B]D=1282022.01 | 1.28 | |
| [SCW2B]D=642022.01 | 0.59 | |
| [SCW2B]D=322022.01 | 0.43 | |
| Wasserstein Iterative NetworksD=1282022.01 | 0.38 | |
| [SCW2B]D=162022.01 | 0.28 | |
| Wasserstein Iterative NetworksD=642022.01 | 0.23 | |
| [SCW2B]D=82022.01 | 0.16 | |
| Wasserstein Iterative NetworksD=322022.01 | 0.11 | |
| [SCW2B]D=42022.01 | 0.09 | |
| Wasserstein Iterative NetworksD=162022.01 | 0.08 | |
| [SCW2B]D=22022.01 | 0.07 | |
| Wasserstein Iterative NetworksD=42022.01 | 0.02 | |
| Wasserstein Iterative NetworksD=22022.01 | 0.01 | |
| Wasserstein Iterative NetworksD=82022.01 | 0.01 |