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Wasserstein Distance Approximation on ShapeNet V2
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0.95
R^2
RG-se
0.638
0.719
0.8
0.881
Sep 24, 2025
R^2
MSE
MAE
Updated 1mo ago
Evaluation Results
Method
Method
Links
R^2
MSE
MAE
RG-se
Training set size=100,...
2025.09
0.95
9.9
7.8
RG-seo
Training set size=100,...
2025.09
0.95
9.8
7.8
RG-s
Training set size=100,...
2025.09
0.94
1.1
8.2
RG-se
Training set size=100,...
2025.09
0.92
1.4
9.3
RG-e
Training set size=100,...
2025.09
0.92
1.5
9.8
RG-seo
Training set size=100,...
2025.09
0.91
1.7
1
RG-e
Training set size=100,...
2025.09
0.9
1.7
1
RG-s
Training set size=100,...
2025.09
0.88
2
1.1
RG-o
Training set size=100,...
2025.09
0.75
3.8
1.6
RG-o
Training set size=100,...
2025.09
0.66
5.2
1.8
Wormhole
Training set size=100
2025.09
0.65
6.6
1.8
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