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Active Learning Regression on PartMC target χa (test)

0.7621R^2CAAL
0.6122360.6511430.690050.728957Feb 12, 2026

Evaluation results

MethodLinks
CAALAL rounds=262026.020.76219.40.0642-11.8354.445.6
CAALBackbone=FT-Transformer2026.020.76219.40.0642-11.8354.445.6
CoresetAL rounds=262026.020.7588.820.0646-11.2551.148.9
LCMDAL rounds=262026.020.75348.160.0653-10.2487.822.2
ALM (Entropy)AL rounds=262026.020.74687.210.0662-9.0571.128.9
BALDAL rounds=262026.020.7456.940.0665-8.7157.842.2
BALDBackbone=FT-Transformer, AL Strategy=Uncertainty-based2026.020.74066.310.067-7.9357.842.2
QBC (Epi)AL rounds=262026.020.73655.730.0676-7.2161.138.9
QBCBackbone=FT-Transformer, Variant=Epi, AL Strategy=Uncertainty-based2026.020.73655.730.0676-7.2261.138.9
RandomAL rounds=262026.020.73635.70.0676-7.1867.832.2
BADGEAL rounds=262026.020.73545.560.0677-7.0157.842.2
RandomBackbone=FT-Transformer2026.020.73134.980.0682-6.367.832.2
AleAL rounds=262026.020.72714.380.0687-5.5761.138.9
ALMBackbone=FT-Transformer, Variant=Entropy, AL Strategy=Uncertainty-based2026.020.72484.050.069-5.1871.128.9
ConfidenceAL rounds=262026.020.71993.340.0697-4.3397.82.2
BADGEBackbone=FT-Transformer, AL Strategy=Geometry/Representation-based2026.020.71682.90.07-3.8157.842.2
CoresetBackbone=FT-Transformer, AL Strategy=Geometry/Representation-based2026.020.71084.670.0685-5.9351.148.9
AleBackbone=FT-Transformer, AL Strategy=Uncertainty-based (Aleatoric)2026.020.70411.080.0716-1.6861.138.9
Full Data (χa)AL rounds=N/A2026.020.6966—0.0728—1000
Full Data (Ref.)Backbone=FT-Transformer2026.020.6966—0.0728—1000
LCMDBackbone=FT-Transformer, AL Strategy=Geometry/Representation-based2026.020.6817-2.140.07431.98——
ConfidenceBackbone=FT-Transformer, AL Strategy=Uncertainty-based2026.020.618-11.280.081311.73——