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Regression on ELEVATORS (test)

0.0029RMSEeM-KOFL
-0.0173630.1195480.256460.393372Oct 4, 2022Jan 5, 2023Apr 8, 2023Jul 10, 2023Oct 11, 2023Jan 12, 2024Apr 15, 2024

Evaluation results

MethodLinks
eM-KOFL2024.040.0029—0.0445—
FOMD-OMSJ=22024.040.0032—0.0087—
POF-MKL2024.040.0081—0.052—
DKL2023.060.084———
CIBERstage=SECOND2023.060.088———
CIBERstage=LAST2023.060.088———
SWAG2023.060.088———
PCA+VImode=SI2023.060.088———
PCA+ESSmode=SI2023.060.089———
FF2023.060.089———
ORTHVGP2023.060.095———
NL2023.060.101———
SGD2023.060.103———
MATÉRN (BBMM)n=10623, d=18, GPU=Tesla V100-SXM2-32GB, Feature transformation=ECDF, Precision=Pnew2022.100.3940.619——
SVGPn=10623, d=18, GPU=Tesla V100-SXM2-32GB, Feature transformation=ECDF, Precision=Pnew2022.100.3990.519——
SGPRn=10623, d=18, GPU=Tesla V100-SXM2-32GB, Feature transformation=ECDF, Precision=Pnew2022.100.4370.58——
BTn=10623, d=18, GPU=Tesla V100-SXM2-16GB, Feature transformation=ECDF, Precision=Pnew2022.100.4760.646——
BTEn=10623, d=18, GPU=Tesla V100-SXM2-16GB, Feature transformation=ECDF, Precision=Pnew2022.100.4780.649——
Simplex-GPn=10623, d=18, GPU=Tesla V100-SXM2-32GB, Feature transformation=ECDF, Precision=Pnew2022.100.511.6——
CIBERcollapsed parameter set=second-to-last layer2023.06———-0.378
CIBERcollapsed parameter set=last layer2023.06———-0.371
CNPDeployment=Factorised prediction2026.02———-0.9417
CNPdeployment=Factorised2026.02———-1.264
incTNPDeployment=Factorised prediction2026.02———-0.0235
incTNPdeployment=Factorised2026.02———-0.346
incTNP-SeqDeployment=Factorised prediction2026.02———-0.0086
incTNP-Seqdeployment=Factorised2026.02———-0.331
LBANPDeployment=Factorised prediction2026.02———-0.2048
LBANPdeployment=Factorised2026.02———-0.527
NL2023.06———-0.698
OrthVGP2023.06———-0.448
PCA+ESSvariant=SI2023.06———-0.331
PCA+VIvariant=SI2023.06———-0.325
SGD2023.06———-0.538
SWAG2023.06———-0.374
TNP-DDeployment=Factorised prediction2026.02———-0.3219
TNP-Ddeployment=Factorised2026.02———-0.322