Browse › Graphs › Graph Classification › COLLAB

Graph Classification archive 2025-07-28

COLLAB Benchmark (Graph Classification)

39 rows 34 with code listed 2 metrics Dataset page

Graph Classification is a task that involves classifying a graph-structured data into different classes or categories. Graphs are a powerful way to represent relationships and interactions between different entities, and graph classification can be applied to a wide range of applications, such as social network analysis, bioinformatics, and recommendation systems. In graph classification, the input is a graph, and the goal is to learn a classifier that can accurately predict the class of the graph.

The archive carries no text for this table; the description above is the archive's text for the task Graph Classification. archive 2025-07-28

Over time archive 2025-07-28

The chart needs JavaScript; the table below carries every value.

Direction inferred from the metric name, not from the archive: Accuracy (higher is better), Accuracy (10-fold) (higher is better). Points are placed at the row's paper date; 39 of 39 rows carry one.

Results archive 2025-07-28

Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.

Paper Code Ran Syntology Report
1 U2GNN (Unsupervised) 95.62% – Paper Code 2019 4 of 4 ran · 0 unverified report
2 TFGW ADJ (L=2) 84.3% – Paper Code 2022 linked, not harvested report
3 DUGNN 84.20% ✓ Paper Code 2019 linked, not harvested report
4 G_DenseNet 83.16% – Paper – 2018 no code linked report
5 GFN 81.50% – Paper Code 2019 linked, not harvested report
6 PPGN 81.38% – Paper Code 2019 0 of 8 ran · 8 unverified report
7 GFN-light 81.34% – Paper Code 2019 linked, not harvested report
8 FactorGCN 81.2%81.2% – Paper Code 2020 2 of 2 ran · 0 unverified report
9 GMT 80.74% – Paper Code 2021 4 of 5 ran · 1 unverified report
10 sGIN 80.71% – Paper Code 2019 linked, not harvested report
11 GCN 80.6% – Paper Code 2019 0 of 2 ran · 2 unverified report
12 Self-supervised GraphMAE 80.32% – Paper Code 2022 2 of 3 ran · 1 unverified report
13 GIN-0 80.2% – Paper Code 2018 3 of 10 ran · 7 unverified report
14 WEGL 79.8% – Paper Code 2020 linked, not harvested report
15 MEWISPool 79.66% – Paper Code 2021 2 of 2 ran · 0 unverified report
16 CapsGNN 79.62% – Paper Code 2019 linked, not harvested report
17 Local Topological Profile (LTP) 79.4 ± 2.579.4 ± 2.5 – Paper Code 2023 linked, not harvested report
18 NDP 79.1% – Paper Code 2019 1 of 1 ran · 0 unverified report
19 SEG-BERT 78.42% – Paper Code 2020 linked, not harvested report
20 U2GNN 77.84% – Paper Code 2019 4 of 4 ran · 0 unverified report
21 R-GIN + PANDA 77.8% – Paper Code 2024 7 of 9 ran · 2 unverified report
22 Graph U-Nets 77.56% – Paper Code 2019 3 of 4 ran · 1 unverified report
23 hGANet 77.48% – Paper Code 2019 linked, not harvested report
24 GNN (DiffPool) 75.48% – Paper Code 2018 1 of 20 ran · 19 unverified report
25 GIN + PANDA 75.11% – Paper Code 2024 7 of 9 ran · 2 unverified report
26 GraphSAGE 73.9% – Paper Code 2019 linked, not harvested report
27 DGCNN 73.76% – Paper Code 2018 linked, not harvested report
28 DGK 73.09% – Paper – 2015 no code linked report
29 DiffWire 72.24% – Paper Code 2022 linked, not harvested report
30 2D CNN 71.76% – Paper – 2017 no code linked report
31 R-GCN + PANDA 71.4% – Paper Code 2024 7 of 9 ran · 2 unverified report
32 CT-Layer 69.87% – Paper Code 2022 linked, not harvested report
33 DGCNN (sum) 69.45% – Paper Code 2018 linked, not harvested report
34 GCN + PANDA 68.4% – Paper Code 2024 7 of 9 ran · 2 unverified report
35 DGCNN 68.34% – Paper – 2017 no code linked report
36 Weak-supervised ChebyNet 66.97% – Paper Code 2019 linked, not harvested report
37 GAP-Layer (Ncut) 65.89% – Paper Code 2022 linked, not harvested report
38 1-NMFPool 65.0% – Paper – 2019 no code linked report
39 GAP-Layer (Rcut) 64.47% – Paper Code 2022 linked, not harvested report

All 39 rows shown. 39 link to a paper page on this site; 1 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28

Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 16 rows have a graph line, from 12 distinct papers; 14 rows (10 papers) have at least one sample that ran. Counting each paper once: Syntology ran 29 of 70 samples; 41 unverified. Separately, 18 of those 70 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-24. Per-sample status is on the paper page.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections