Codesota · Models · ChebGAT-GCNAcademic2 results · 1 benchmarks
Model card

ChebGAT-GCN.

AcademicclassificationChebyshev Spectral GCN + Graph Attention Network1 current SOTA

Enhanced GCN combining Chebyshev Spectral Graph Convolution and Graph Attention Networks (GAT) with multi-branch architecture for multimodal neuroimaging. Submitted Nov 2025.

§ 02 · Benchmarks

Every benchmark ChebGAT-GCN has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01ABIDE IMedical · Disease Classificationauc82.0%#1/92025-11-27source ↗
02ABIDE IMedical · Disease Classificationaccuracy74.8%#10/242025-11-27source ↗
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area

Where ChebGAT-GCN actually performs.

Medical
1
benchmark
avg rank #5.5 · 1 SOTA
§ 04 · Papers

1 paper with results for ChebGAT-GCN.

  1. 2025-11-27· 2 results

    Enhanced Graph Convolutional Network with Chebyshev Spectral Convolution and Graph Attention Networks for Autism Spectrum Disorder Classification

§ 05 · Related models

Other Academic models scored on Codesota.

BrainTWT
2 results
Causal fMRI Model
2 results
DNTextSpotter (ResNet-50)
2 results
DNTextSpotter (ViTAEv2-S)
2 results
IAST
2 results
LRANet++
2 results
LSGSpotter
2 results
SwinTextSpotter v2
2 results
§ 06 · Sources & freshness

Where these numbers come from.

paper
2
results
2 of 2 rows marked verified.