Regression on Energy (Predictive MSE, Test Log Likelihood)
1.4NLLGP
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| GPExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=322026.07 | 1.4 | — | — | |
| BDKNExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 1.73 | — | — | |
| VBLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 1.96 | — | — | |
| DEExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 2.79 | — | — | |
| MFVIExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 3.27 | — | — | |
| LDBLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 3.39 | — | — | |
| DKLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 3.42 | — | — | |
| BLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.07 | 3.44 | — | — | |
| SVGPModel Variant=SVGP2024.08 | — | 2.02 | 156 | |
| SVGP+TModel Variant=SVGP+T2024.08 | — | 1.12 | 92.4 | |
| SVTP+MCModel Variant=SVTP+MC2024.08 | — | 0.84 | 70.5 | |
| SVTP+UBModel Variant=SVTP+UB2024.08 | — | 0.74 | 63.3 |