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ResearchFormerly WizWand

Torque 1 prediction on SARCOS robot arm (test)

10.7RMSEAugmented
9.93615.09320.2525.407Oct 18, 2022
Updated 8mo ago

Evaluation results

MethodLinks
AugmentedNumber of training samples=502022.1010.7
DirectNumber of training samples=502022.1010.8
AffineTL-constNumber of training samples=502022.1010.9
AffineTL-fullNumber of training samples=502022.1011.1
Fine-tuneNumber of training samples=502022.1011.1
L2-SPNumber of training samples=502022.1011.6
AugmentedNumber of training samples=402022.1011.9
DirectNumber of training samples=402022.1012.2
AffineTL-constNumber of training samples=402022.1012.2
AffineTL-fullNumber of training samples=402022.1012.3
Fine-tuneNumber of training samples=402022.1012.6
L2-SPNumber of training samples=402022.1013
AugmentedNumber of training samples=302022.1013.3
AffineTL-constNumber of training samples=302022.1013.4
MAMLNumber of training samples=502022.1013.4
DirectNumber of training samples=302022.1013.7
AffineTL-fullNumber of training samples=302022.1013.7
Fine-tuneNumber of training samples=302022.1014.1
MAMLNumber of training samples=402022.1014.4
L2-SPNumber of training samples=302022.1014.5
HTL-offsetNumber of training samples=402022.1015
HTL-offsetNumber of training samples=502022.1015.1
AugmentedNumber of training samples=202022.1015.7
DirectNumber of training samples=202022.1015.8
AffineTL-fullNumber of training samples=202022.1015.9
AffineTL-constNumber of training samples=202022.1015.9
HTL-offsetNumber of training samples=302022.1016.2
HTL-scaleNumber of training samples=502022.1016.7
MAMLNumber of training samples=302022.1016.7
HTL-scaleNumber of training samples=402022.1016.9
PAC-NetNumber of training samples=502022.1017.1
Only sourceNumber of training samples=502022.1017.3
DirectNumber of training samples=152022.1017.4
Only sourceNumber of training samples=402022.1017.6
HTL-scaleNumber of training samples=302022.1017.6
Fine-tuneNumber of training samples=202022.1017.6
PAC-NetNumber of training samples=402022.1017.6
AffineTL-constNumber of training samples=152022.1017.7
AugmentedNumber of training samples=152022.1017.8
HTL-offsetNumber of training samples=202022.1017.8
L2-SPNumber of training samples=202022.1018
Only sourceNumber of training samples=302022.1018.5
HTL-scaleNumber of training samples=202022.1018.5
PAC-NetNumber of training samples=302022.1018.5
AffineTL-fullNumber of training samples=152022.1018.6
Fine-tuneNumber of training samples=152022.1018.6
AffineTL-fullNumber of training samples=102022.1018.8
AffineTL-constNumber of training samples=102022.1018.8
L2-SPNumber of training samples=152022.1018.8
DirectNumber of training samples=102022.1018.9
AugmentedNumber of training samples=102022.1019.2
Only sourceNumber of training samples=202022.1019.7
HTL-offsetNumber of training samples=152022.1019.8
PAC-NetNumber of training samples=202022.1020.1
MAMLNumber of training samples=202022.1020.3
HTL-scaleNumber of training samples=152022.1020.4
Fine-tuneNumber of training samples=102022.1020.5
L2-SPNumber of training samples=102022.1020.5
PAC-NetNumber of training samples=152022.1020.7
MAMLNumber of training samples=152022.1020.8
Only sourceNumber of training samples=152022.1021
HTL-offsetNumber of training samples=102022.1021.2
AffineTL-fullNumber of training samples=52022.1021.2
AffineTL-constNumber of training samples=52022.1021.2
DirectNumber of training samples=52022.1021.3
Only sourceNumber of training samples=52022.1021.8
HTL-scaleNumber of training samples=102022.1022.1
Only sourceNumber of training samples=102022.1022.3
MAMLNumber of training samples=102022.1022.5
PAC-NetNumber of training samples=102022.1022.7
HTL-scaleNumber of training samples=52022.1023.3
HTL-offsetNumber of training samples=52022.1023.7
AugmentedNumber of training samples=52022.1024
L2-SPNumber of training samples=52022.1024.9
Fine-tuneNumber of training samples=52022.1025
PAC-NetNumber of training samples=52022.1025.2
MAMLNumber of training samples=52022.1029.8