LD-weighted PDF reconstruction on three-mode NLS Uniform distribution (test)
0KL DivergenceRC
Evaluation results
| Method | Links | |
|---|---|---|
| RCNumber of training trajectories N=5002026.04 | 0 | |
| RCNumber of training trajectories N=2502026.04 | 0.0001 | |
| RCNumber of training trajectories N=1252026.04 | 0.0002 | |
| RCNumber of training trajectories N=10002026.04 | 0.0004 | |
| GHNNNumber of training trajectories N=10002026.04 | 0.0019 | |
| GHNNNumber of training trajectories N=2502026.04 | 0.0019 | |
| SympNetNumber of training trajectories N=1252026.04 | 0.0021 | |
| SympNetNumber of training trajectories N=5002026.04 | 0.0024 | |
| SympNetNumber of training trajectories N=2502026.04 | 0.0028 | |
| SympNetNumber of training trajectories N=10002026.04 | 0.0034 | |
| GHNNNumber of training trajectories N=5002026.04 | 0.0035 | |
| HénonNetNumber of training trajectories N=1252026.04 | 0.0036 | |
| HénonNetNumber of training trajectories N=2502026.04 | 0.0036 | |
| HénonNetNumber of training trajectories N=5002026.04 | 0.0037 | |
| GHNNNumber of training trajectories N=1252026.04 | 0.0039 | |
| HénonNetNumber of training trajectories N=10002026.04 | 0.0118 |