List your company
ResearchFormerly WizWand

Image Classification on MNIST CS 100 (test)

91.52Mean AccuracyGIW
48.401659.595870.7981.9842May 24, 2023
Updated 8mo ago

Evaluation results

MethodLinks
GIWShift type=Class-prior Shift, Shift intensity=100, Case=iii, Trials=52023.0591.52
GIW2023.0587.14
GIWShift Scenario=Case (iv)2023.0587.14
Pretrain-valShift type=Class-prior Shift, Shift intensity=100, Case=iii, Trials=52023.0584.54
Pretrain-val2023.0582.09
Pretrain-valShift Scenario=Case (iv)2023.0582.09
ReweightShift type=Class-prior Shift, Shift intensity=100, Case=iii, Trials=52023.0580.65
Val-only2023.0579.86
Val-onlyShift Scenario=Case (iv)2023.0579.86
Val-onlyShift type=Class-prior Shift, Shift intensity=100, Case=iii, Trials=52023.0578.94
DIWShift type=Class-prior Shift, Shift intensity=100, Case=iii, Trials=52023.0578.58
MW-NetShift type=Class-prior Shift, Shift intensity=100, Case=iii, Trials=52023.0577.06
R-DIWShift type=Class-prior Shift, Shift intensity=100, Case=iii, Trials=52023.0576.53
Reweight2023.0574.84
DIW2023.0573.66
MW-Net2023.0571.42
R-DIW2023.0571.11
CCSAShift Scenario=Case (iv)2023.0566.31
DANNShift Scenario=Case (iv)2023.0550.06