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3D Chern-Simons prediction on Kühn 3-torus L=8 (test)

0.99R^2Adjusted cup-product layer
-0.18520.11990.4250.7301Jun 11, 2026
Updated 4mo ago

Evaluation results

MethodLinks
Adjusted cup-product layerM (Training set size)=642026.060.99
Adjusted cup-product layerM (Training set size)=2562026.060.99
Adjusted cup-product layerM (Training set size)=10242026.060.99
Adjusted cup-product layerM (Training set size)=40962026.060.99
Adjusted cup-product layerM (Training set size)=163842026.060.99
CNN-3DM (Training set size)=163842026.060.21
CNN-3DM (Training set size)=40962026.060.08
FAKE-FLAT (κ=0)M (Training set size)=163842026.060
GNNM (Training set size)=2562026.060
GNNM (Training set size)=10242026.060
GNNM (Training set size)=40962026.060
GNNM (Training set size)=163842026.060
MPSN-SINM (Training set size)=2562026.060
MPSN-SINM (Training set size)=10242026.060
MPSN-SINM (Training set size)=40962026.060
MPSN-SINM (Training set size)=163842026.060
SNN-EbliM (Training set size)=2562026.060
SNN-EbliM (Training set size)=10242026.060
SNN-EbliM (Training set size)=40962026.060
SNN-EbliM (Training set size)=163842026.060
CNN-3DM (Training set size)=2562026.060
CNN-3DM (Training set size)=10242026.060
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