3D Chern-Simons prediction on Kühn 3-torus L=8 (test)
0.99R^2Adjusted cup-product layer
Evaluation Results
| Method | Links | |
|---|---|---|
| Adjusted cup-product layerM (Training set size)=642026.06 | 0.99 | |
| Adjusted cup-product layerM (Training set size)=2562026.06 | 0.99 | |
| Adjusted cup-product layerM (Training set size)=10242026.06 | 0.99 | |
| Adjusted cup-product layerM (Training set size)=40962026.06 | 0.99 | |
| Adjusted cup-product layerM (Training set size)=163842026.06 | 0.99 | |
| CNN-3DM (Training set size)=163842026.06 | 0.21 | |
| CNN-3DM (Training set size)=40962026.06 | 0.08 | |
| FAKE-FLAT (κ=0)M (Training set size)=163842026.06 | 0 | |
| GNNM (Training set size)=2562026.06 | 0 | |
| GNNM (Training set size)=10242026.06 | 0 | |
| GNNM (Training set size)=40962026.06 | 0 | |
| GNNM (Training set size)=163842026.06 | 0 | |
| MPSN-SINM (Training set size)=2562026.06 | 0 | |
| MPSN-SINM (Training set size)=10242026.06 | 0 | |
| MPSN-SINM (Training set size)=40962026.06 | 0 | |
| MPSN-SINM (Training set size)=163842026.06 | 0 | |
| SNN-EbliM (Training set size)=2562026.06 | 0 | |
| SNN-EbliM (Training set size)=10242026.06 | 0 | |
| SNN-EbliM (Training set size)=40962026.06 | 0 | |
| SNN-EbliM (Training set size)=163842026.06 | 0 | |
| CNN-3DM (Training set size)=2562026.06 | 0 | |
| CNN-3DM (Training set size)=10242026.06 | 0 | |
| FAKE-FLAT (κ=0)M (Training set size)=40962026.06 | -0.01 | |
| GNNM (Training set size)=642026.06 | -0.01 | |
| CNN-3DM (Training set size)=642026.06 | -0.01 | |
| MPSN-SINM (Training set size)=642026.06 | -0.03 | |
| SNN-EbliM (Training set size)=642026.06 | -0.03 | |
| FAKE-FLAT (κ=0)M (Training set size)=642026.06 | -0.07 | |
| FAKE-FLAT (κ=0)M (Training set size)=2562026.06 | -0.07 | |
| FAKE-FLAT (κ=0)M (Training set size)=10242026.06 | -0.14 |