Hypergraph Benchmarks

Senate

Node Classification

2-class node classification US Senate voting hypergraph node classification (2 classes). Uses node-hyperedge incidence and the released node features. Clique expansion changes the input by discarding hyperedge identity. Evaluated by Accuracy.

Dataset details

Task

US Senate voting hypergraph node classification (2 classes). The primary catalog metric is Accuracy.

Data

US Senate voting hypergraph node classification (2 classes). The cataloged artifact reports 1 graphs, 2 target classes or tasks.

Features

The release represents higher-order membership with a node-hyperedge incidence relation and supplies node features where available. Some source datasets have no measured features and use documented synthetic features; clique expansion is an alternative representation that discards hyperedge identity.

Splits and evaluation

The catalog records these protocols or variants: Standard split. Evaluation uses Accuracy (higher is better). Exact masks or folds must come from the cited release.

Quirks and pitfalls

Do not silently replace incidence propagation with clique expansion or merge distinct releases sharing a short name. Random synthetic features, split seeds, hyperedge multiplicity, and isolated-node handling can dominate results and must be reported.

Sources

SOTA Progression

new SOTA matches SOTA at that time other proposed result other baseline result

Leaderboard

#ModelAccuracy ↑Paper
1
HealHGNN
0.7606 ± 0.0413
2
KHGNN
0.7123 ± 0.0394
3
AllSetTransformer
0.6933 ± 0.0220
4
SheafHyperGNN
0.6873 ± 0.0468
5
Deep-HGNN
0.6839 ± 0.0479
6
PhenomNN
0.6770 ± 0.0524
7
FrameHGNN
0.6761 ± 0.0527
8
ED-HNN
0.6479 ± 0.0514
9
HNHN
0.5093 ± 0.0633
10
HyperGCN
0.5013 ± 0.0321
11
UniGCNII
0.4930 ± 0.0425
12
HCHA
0.4862 ± 0.0441
13
HGNN
0.4859 ± 0.0452
14
AllDeepSets
0.4817 ± 0.0567
SOTA performance set a new SOTA at the time matched the SOTA at the time