ML Research Wiki / Benchmarks / Node Classification / Cornell (60%/20%/20% random splits)

Cornell (60%/20%/20% random splits)

Node Classification Benchmark

Performance Over Time

📊 Showing 36 results | 📏 Metric: 1:1 Accuracy

Top Performing Models

Rank	Model	Paper	1:1 Accuracy	Date	Code
1	Geom-GCN*	Geom-GCN: Geometric Graph Convolutional Networks	60.81	2020-02-13	📦 bingzhewei/geom-gcn 📦 graphdml-uiuc-jlu/geom-gcn 📦 alexfanjn/geomgcn_pyg 📦 KAIDI3270/Geom_GCN_pytorch_implementation
2	ACM-SGC-2	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN
3	ACMII-GCN	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN
4	ACMII-Snowball-2	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN
5	ACM-Snowball-2	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN
6	ACM-GCN+	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN
7	ACM-GCN	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN
8	ACM-Snowball-3	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN
9	ACM-GCN++	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN
10	ACMII-GCN+	Revisiting Heterophily For Graph Neural Networks	0.00	2022-10-14	📦 SitaoLuan/ACM-GNN

All Papers (36)

Geom-GCN: Geometric Graph Convolutional Networks

2020

Geom-GCN*

bingzhewei/geom-gcn graphdml-uiuc-jlu/geom-gcn

Revisiting Heterophily For Graph Neural Networks

2022

ACM-SGC-2

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACMII-GCN

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACMII-Snowball-2

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACM-Snowball-2

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACM-GCN+

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACM-GCN

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACM-Snowball-3

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACM-GCN++

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACMII-GCN+

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACM-SGC-1

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACMII-Snowball-3

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACM-GCNII*

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACM-GCNII

SitaoLuan/ACM-GNN

Revisiting Heterophily For Graph Neural Networks

2022

ACMII-GCN++

SitaoLuan/ACM-GNN

BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation

2021

BernNet

ivam-he/BernNet

Predict then Propagate: Graph Neural Networks meet Personalized PageRank

2018

APPNP

dmlc/dgl dmlc/dgl

Adaptive Universal Generalized PageRank Graph Neural Network

2020

GPRGNN

jianhao2016/GPRGNN

Revisiting Heterophily For Graph Neural Networks

2022

MLP-2

SitaoLuan/ACM-GNN

Simple and Deep Graph Convolutional Networks

2020

GCNII*

chennnM/GCNII chennnM/GCNII

Simple and Deep Graph Convolutional Networks

2020

GCNII

chennnM/GCNII chennnM/GCNII

Beyond Low-frequency Information in Graph Convolutional Networks

2021

FAGCN

bdy9527/FAGCN

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

2020

H2GCN

GemsLab/H2GCN GitEventhandler/H2GCN-PyTorch

Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks

2019

Snowball-3

PwnerHarry/Stronger_GCN

Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks

2019

Snowball-2

PwnerHarry/Stronger_GCN

Semi-Supervised Classification with Graph Convolutional Networks

2016

GCN

dmlc/dgl dmlc/dgl

Graph Attention Networks

2017

GAT

labmlai/annotated_deep_learning_paper_implementations dmlc/dgl

Half-Hop: A graph upsampling approach for slowing down message passing

2023

HH-GraphSAGE

nerdslab/halfhop

Revisiting Heterophily For Graph Neural Networks

2022

GAT+JK

SitaoLuan/ACM-GNN

Half-Hop: A graph upsampling approach for slowing down message passing

2023

HH-GAT

nerdslab/halfhop

Simplifying Graph Convolutional Networks

2019

SGC-2

dmlc/dgl dmlc/dgl

Inductive Representation Learning on Large Graphs

2017

GraphSAGE

pyg-team/pytorch_geometric dmlc/dgl

Simplifying Graph Convolutional Networks

2019

SGC-1

dmlc/dgl dmlc/dgl

Revisiting Heterophily For Graph Neural Networks

2022

GCN+JK

SitaoLuan/ACM-GNN

Half-Hop: A graph upsampling approach for slowing down message passing

2023

HH-GCN

nerdslab/halfhop

MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing

2019

MixHop

dmlc/dgl benedekrozemberczki/MixHop-and-N-GCN samihaija/mixhop

Model	Paper	1:1 Accuracy	Date
Geom-GCN*	Geom-GCN: Geometric Graph Convolutional Networks	60.81	2020-02-13
ACM-SGC-2	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACMII-GCN	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACMII-Snowball-2	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACM-Snowball-2	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACM-GCN+	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACM-GCN	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACM-Snowball-3	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACM-GCN++	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACMII-GCN+	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACM-SGC-1	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACMII-Snowball-3	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACM-GCNII*	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACM-GCNII	Revisiting Heterophily For Graph Neural Networks		2022-10-14
ACMII-GCN++	Revisiting Heterophily For Graph Neural Networks		2022-10-14
BernNet	BernNet: Learning Arbitrary Graph Spectral Filter…		2021-06-21
APPNP	Predict then Propagate: Graph Neural Networks mee…		2018-10-14
GPRGNN	Adaptive Universal Generalized PageRank Graph Neu…		2020-06-14
MLP-2	Revisiting Heterophily For Graph Neural Networks		2022-10-14
GCNII*	Simple and Deep Graph Convolutional Networks		2020-07-04
GCNII	Simple and Deep Graph Convolutional Networks		2020-07-04
FAGCN	Beyond Low-frequency Information in Graph Convolu…		2021-01-04
H2GCN	Beyond Homophily in Graph Neural Networks: Curren…		2020-06-20
Snowball-3	Break the Ceiling: Stronger Multi-scale Deep Grap…		2019-06-05
Snowball-2	Break the Ceiling: Stronger Multi-scale Deep Grap…		2019-06-05
GCN	Semi-Supervised Classification with Graph Convolu…		2016-09-09
GAT	Graph Attention Networks		2017-10-30
HH-GraphSAGE	Half-Hop: A graph upsampling approach for slowing…		2023-08-17
GAT+JK	Revisiting Heterophily For Graph Neural Networks		2022-10-14
HH-GAT	Half-Hop: A graph upsampling approach for slowing…		2023-08-17
SGC-2	Simplifying Graph Convolutional Networks		2019-02-19
GraphSAGE	Inductive Representation Learning on Large Graphs		2017-06-07
SGC-1	Simplifying Graph Convolutional Networks		2019-02-19
GCN+JK	Revisiting Heterophily For Graph Neural Networks		2022-10-14
HH-GCN	Half-Hop: A graph upsampling approach for slowing…		2023-08-17
MixHop	MixHop: Higher-Order Graph Convolutional Architec…		2019-04-30

Cornell (60%/20%/20% random splits)

Performance Over Time

Edit Benchmark Results

Edit Result

Top Performing Models

All Papers (36)