Toy Regression on toy regression example 2 (test)
1.128RMSE m(·)NE-GMM
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| NE-GMMbatch size=32, feature extractor=single-layer neural network (50 hidden units, Tanh activations)2026.03 | 1.128 | 0.778 | 0.095 | |
| β-NLLbatch size=32, feature extractor=single-layer neural network (50 hidden units, Tanh activations)2026.03 | 1.903 | 12.535 | — | |
| Ensemble-NNbatch size=32, feature extractor=single-layer neural network (50 hidden units, Tanh activations)2026.03 | 2.064 | 12.9 | — | |
| NGBoostbatch size=32, feature extractor=single-layer neural network (50 hidden units, Tanh activations)2026.03 | 4.362 | 12.4 | — | |
| MDNbatch size=32, feature extractor=single-layer neural network (50 hidden units, Tanh activations)2026.03 | 10.767 | 4.735 | 0.382 | |
| SampleNetbatch size=32, feature extractor=single-layer neural network (50 hidden units, Tanh activations)2026.03 | 15.054 | 7.454 | — |