Classification on Vehicle (UCI) (test)
0.422NLLDIMS
Evaluation results
| Method | Links | |
|---|---|---|
| DIMSNumber of samples (S)=30, Number of seeds=5, backbone=3-layer network, hidden units=16, activations=SiLU, dropout=50%2026.05 | 0.422 | |
| RIEM-LAPrior precision=optimized, Number of MC samples=302023.06 | 0.454 | |
| LINEARIZED RIEM-LAPrior precision=optimized, Number of MC samples=302023.06 | 0.494 | |
| RLANumber of samples (S)=30, Number of seeds=5, backbone=3-layer network, hidden units=16, activations=SiLU, dropout=50%2026.05 | 0.776 | |
| LINEARIZED LAPrior precision=optimized, Number of MC samples=302023.06 | 0.875 | |
| MAPPrior precision=optimized, Number of MC samples=302023.06 | 0.975 | |
| VANILLA LAPrior precision=optimized, Number of MC samples=302023.06 | 1.209 | |
| LINLANumber of samples (S)=30, Number of seeds=5, backbone=3-layer network, hidden units=16, activations=SiLU, dropout=50%2026.05 | 5.446 | |
| LANumber of samples (S)=30, Number of seeds=5, backbone=3-layer network, hidden units=16, activations=SiLU, dropout=50%2026.05 | 17.852 |