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Regression on Wine (NLL, RMSE)

0.86NLLGP
0.76161.42582.092.7542May 15, 2024Sep 22, 2024Jan 31, 2025Jun 10, 2025Oct 19, 2025Feb 26, 2026Jul 7, 2026

Evaluation results

MethodLinks
GPExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=322026.070.86—
GPExperimental Setting=2, Learning Rate Setting=low2026.070.860.56
DEvidential2024.050.890.61
NGBoost2024.050.910.63
MCDropout2024.050.930.62
DEnsemble2024.050.940.64
MFVIExperimental Setting=2, Learning Rate Setting=low2026.070.940.63
WEvidential2024.050.950.61
BDKNExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.070.98—
DKLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.070.98—
BLLExperimental Setting=2, Learning Rate Setting=low2026.071.020.64
LDBLLExperimental Setting=2, Learning Rate Setting=low2026.071.030.65
VBLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.071.08—
DEExperimental Setting=2, Learning Rate Setting=low2026.071.110.63
MFVIExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.071.12—
DKLExperimental Setting=2, Learning Rate Setting=low2026.071.160.76
BLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.071.19—
DEExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.071.59—
BDKNExperimental Setting=2, Learning Rate Setting=low2026.071.640.65
CDropout2024.051.70.62
LDBLLExperimental Setting=1 (high learning rate), Learning Rate=0.1, Epochs=40, Batch Size=32, Architecture=2 hidden layers (50 neurons each)2026.072.07—
VBLLExperimental Setting=2, Learning Rate Setting=low2026.073.320.72