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ResearchFormerly WizWand

Regression on Power (NLL)

2.83NLLGP
2.66683.76844.875.9716Jul 7, 2026
Updated 3mo ago

Evaluation results

MethodLinks
GPExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=322026.072.83
BDKNExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.072.97
BLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.073.85
MFVIExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.073.88
VBLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.073.97
LDBLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.075.46
DEExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.076.89
DKLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.076.91