ML Research Wiki / Benchmarks / Graph Classification / NCI109

NCI109

Graph Classification Benchmark

Performance Over Time

📊 Showing 33 results | 📏 Metric: Accuracy

Top Performing Models

Rank	Model	Paper	Accuracy	Date	Code
1	WL-OA	On Valid Optimal Assignment Kernels and Applications to Graph Classification	86.30	2016-06-03	-
2	δ-2-LWL	Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings	84.70	2019-04-02	📦 chrsmrrs/sparsewl
3	CIN++	CIN++: Enhancing Topological Message Passing	84.50	2023-06-06	📦 twitter-research/cwn
4	PIN	Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes	84.00	2023-08-13	-
5	Spec-GN	A New Perspective on the Effects of Spectrum in Graph Neural Networks	83.62	2021-12-14	📦 qslim/gnn-spectrum
6	CAN	Cell Attention Networks	83.60	2022-09-16	📦 lrnzgiusti/can
7	GIC	Gaussian-Induced Convolution for Graphs	82.86	2018-11-11	-
8	PPGN	Provably Powerful Graph Networks	82.23	2019-05-27	📦 hadarser/ProvablyPowerfulGraphNetworks_torch 📦 hadarser/ProvablyPowerfulGraphNetworks
9	ECC (5 scores)	Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs	82.14	2017-04-10	📦 rusty1s/pytorch_cluster 📦 mys007/ecc
10	Multigraph ChebNet	Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules	82.00	2018-11-23	📦 bknyaz/graph_nn

All Papers (33)

On Valid Optimal Assignment Kernels and Applications to Graph Classification

2016

WL-OA

Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings

2019

δ-2-LWL

chrsmrrs/sparsewl

CIN++: Enhancing Topological Message Passing

2023

CIN++

twitter-research/cwn

Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes

2023

PIN

A New Perspective on the Effects of Spectrum in Graph Neural Networks

2021

Spec-GN

qslim/gnn-spectrum

Cell Attention Networks

2022

CAN

lrnzgiusti/can

Gaussian-Induced Convolution for Graphs

2018

GIC

Provably Powerful Graph Networks

2019

PPGN

hadarser/ProvablyPowerfulGraphNetworks_torch hadarser/ProvablyPowerfulGraphNetworks

Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs

2017

ECC (5 scores)

rusty1s/pytorch_cluster mys007/ecc

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules

2018

Multigraph ChebNet

bknyaz/graph_nn

Hierarchical Graph Pooling with Structure Learning

2019

HGP-SL

dmlc/dgl cszhangzhen/HGP-SL gsl-benchmark/gslb

When Work Matters: Transforming Classical Network Structures to Graph CNN

2018

G_DenseNet

Graph Convolutional Networks with EigenPooling

2019

EigenGCN-3

alge24/eigenpooling

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity

2019

UGraphEmb-F

yunshengb/UGraphEmb

graph2vec: Learning Distributed Representations of Graphs

2017

Graph2Vec

benedekrozemberczki/karateclub benedekrozemberczki/graph2vec

Self-Attention Graph Pooling

2019

SAGPool_g

dmlc/dgl inyeoplee77/SAGPool walidgeuttala/Synthetic-Benchmark-for-Graph-Classification

Subgraph Networks with Application to Structural Feature Space Expansion

2019

Deep WL SGN(0,1,2)

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

2019

ASAP

malllabiisc/ASAP

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity

2019

UGraphEmb

yunshengb/UGraphEmb

Self-Attention Graph Pooling

2019

SAGPool_h

dmlc/dgl inyeoplee77/SAGPool walidgeuttala/Synthetic-Benchmark-for-Graph-Classification

Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations

2019

BC + Capsules

An end-to-end attention-based approach for learning on graphs

2024

ESA (Edge set attention, no positional encodings)

davidbuterez/edge-set-attention

How Powerful are Graph Neural Networks?

2018

GIN

dmlc/dgl dmlc/dgl

DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks

2021

DropGIN

karolismart/dropgnn

Principal Neighbourhood Aggregation for Graph Nets

2020

PNA

rusty1s/pytorch_geometric dmlc/dgl

Semi-Supervised Classification with Graph Convolutional Networks

2016

GCN

dmlc/dgl dmlc/dgl

How Attentive are Graph Attention Networks?

2021

GATv2

labmlai/annotated_deep_learning_paper_implementations rusty1s/pytorch_geometric

Graph Attention Networks

2017

GAT

labmlai/annotated_deep_learning_paper_implementations dmlc/dgl

Recipe for a General, Powerful, Scalable Graph Transformer

2022

GraphGPS

rampasek/GraphGPS hamed1375/exphormer

Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

2024

S-CGIB

NSLab-CUK/S-CGIB

Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity

2023

UGT

nslab-cuk/unified-graph-transformer nslab-cuk/community-aware-graph-transformer nslab-cuk/literalkg

Do Transformers Really Perform Bad for Graph Representation?

2021

Graphormer

microsoft/Graphormer Microsoft/Graphormer

Pure Transformers are Powerful Graph Learners

2022

TokenGT

jw9730/tokengt luis-mueller/wl-transformers

NCI109

Performance Over Time

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Top Performing Models

All Papers (33)

On Valid Optimal Assignment Kernels and Applications to Graph Classification

Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings

CIN++: Enhancing Topological Message Passing

Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes

A New Perspective on the Effects of Spectrum in Graph Neural Networks

Cell Attention Networks

Gaussian-Induced Convolution for Graphs

Provably Powerful Graph Networks

Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules

Hierarchical Graph Pooling with Structure Learning

When Work Matters: Transforming Classical Network Structures to Graph CNN

Graph Convolutional Networks with EigenPooling

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity

graph2vec: Learning Distributed Representations of Graphs

Self-Attention Graph Pooling

Subgraph Networks with Application to Structural Feature Space Expansion

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity

Self-Attention Graph Pooling

Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations

An end-to-end attention-based approach for learning on graphs

How Powerful are Graph Neural Networks?

DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks

Principal Neighbourhood Aggregation for Graph Nets

Semi-Supervised Classification with Graph Convolutional Networks

How Attentive are Graph Attention Networks?

Graph Attention Networks

Recipe for a General, Powerful, Scalable Graph Transformer

Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity

Do Transformers Really Perform Bad for Graph Representation?

Pure Transformers are Powerful Graph Learners

Model	Paper	Accuracy	Date
WL-OA	On Valid Optimal Assignment Kernels and Applicati…	86.30	2016-06-03
δ-2-LWL	Weisfeiler and Leman go sparse: Towards scalable …	84.70	2019-04-02
CIN++	CIN++: Enhancing Topological Message Passing	84.50	2023-06-06
PIN	Weisfeiler and Lehman Go Paths: Learning Topologi…	84.00	2023-08-13
Spec-GN	A New Perspective on the Effects of Spectrum in G…	83.62	2021-12-14
CAN	Cell Attention Networks	83.60	2022-09-16
GIC	Gaussian-Induced Convolution for Graphs	82.86	2018-11-11
PPGN	Provably Powerful Graph Networks	82.23	2019-05-27
ECC (5 scores)	Dynamic Edge-Conditioned Filters in Convolutional…	82.14	2017-04-10
Multigraph ChebNet	Spectral Multigraph Networks for Discovering and …	82.00	2018-11-23
HGP-SL	Hierarchical Graph Pooling with Structure Learning	80.67	2019-11-14
G_DenseNet	When Work Matters: Transforming Classical Network…	80.66	2018-07-07
EigenGCN-3	Graph Convolutional Networks with EigenPooling	74.90	2019-04-30
UGraphEmb-F	Unsupervised Inductive Graph-Level Representation…	74.48	2019-04-01
Graph2Vec	graph2vec: Learning Distributed Representations o…	74.26	2017-07-17
SAGPool_g	Self-Attention Graph Pooling	74.06	2019-04-17
Deep WL SGN(0,1,2)	Subgraph Networks with Application to Structural …	71.06	2019-03-21
ASAP	ASAP: Adaptive Structure Aware Pooling for Learni…	70.07	2019-11-18
UGraphEmb	Unsupervised Inductive Graph-Level Representation…	69.17	2019-04-01
SAGPool_h	Self-Attention Graph Pooling	67.86	2019-04-17
BC + Capsules	Capsule Neural Networks for Graph Classification …	58.04	2019-02-22
ESA (Edge set attention, no positional encodings)	An end-to-end attention-based approach for learni…		2024-02-16
GIN	How Powerful are Graph Neural Networks?		2018-10-01
DropGIN	DropGNN: Random Dropouts Increase the Expressiven…		2021-11-11
PNA	Principal Neighbourhood Aggregation for Graph Nets		2020-04-12
GCN	Semi-Supervised Classification with Graph Convolu…		2016-09-09
GATv2	How Attentive are Graph Attention Networks?		2021-05-30
GAT	Graph Attention Networks		2017-10-30
GraphGPS	Recipe for a General, Powerful, Scalable Graph Tr…		2022-05-25
S-CGIB	Pre-training Graph Neural Networks on Molecules b…		2025-02-20
UGT	Transitivity-Preserving Graph Representation Lear…		2023-08-18
Graphormer	Do Transformers Really Perform Bad for Graph Repr…		2021-06-09
TokenGT	Pure Transformers are Powerful Graph Learners		2022-07-06