ML Research Wiki / Benchmarks / Node Classification / USA Air-Traffic

USA Air-Traffic

Node Classification Benchmark

Performance Over Time

📊 Showing 7 results | 📏 Metric: Accuracy

Top Performing Models

Rank	Model	Paper	Accuracy	Date	Code
1	DEMO-Net(weight)	DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification	64.70	2019-06-05	📦 jwu4sml/DEMO-Net
2	Planetoid*	Revisiting Semi-Supervised Learning with Graph Embeddings	64.70	2016-03-29	📦 tkipf/gcn 📦 kimiyoung/planetoid 📦 DeepGraphLearning/GMNN
3	GAT (Velickovic et al., 2018)	Graph Attention Networks	58.50	2017-10-30	📦 labmlai/annotated_deep_learning_paper_implementations 📦 dmlc/dgl 📦 dmlc/dgl
4	Union (Li et al., 2018)	Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning	58.20	2018-01-22	📦 liqimai/gcn
5	Intersection (Li et al., 2018)	Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning	57.30	2018-01-22	📦 liqimai/gcn
6	GraphSAGE (Hamilton et al., [2017a])	Inductive Representation Learning on Large Graphs	31.60	2017-06-07	📦 pyg-team/pytorch_geometric 📦 dmlc/dgl 📦 dmlc/dgl
7	UGT	Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity	0.00	2023-08-18	📦 nslab-cuk/unified-graph-transformer 📦 nslab-cuk/community-aware-graph-transformer 📦 nslab-cuk/literalkg

All Papers (7)

DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification

2019

DEMO-Net(weight)

jwu4sml/DEMO-Net

Revisiting Semi-Supervised Learning with Graph Embeddings

2016

Planetoid*

tkipf/gcn kimiyoung/planetoid

Graph Attention Networks

2017

GAT (Velickovic et al., 2018)

labmlai/annotated_deep_learning_paper_implementations dmlc/dgl

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

2018

Union (Li et al., 2018)

liqimai/gcn

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

2018

Intersection (Li et al., 2018)

liqimai/gcn

Inductive Representation Learning on Large Graphs

2017

GraphSAGE (Hamilton et al., [2017a])

pyg-team/pytorch_geometric dmlc/dgl

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

USA Air-Traffic

Performance Over Time

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Top Performing Models

All Papers (7)

DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification

Revisiting Semi-Supervised Learning with Graph Embeddings

Graph Attention Networks

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

Inductive Representation Learning on Large Graphs

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

Model	Paper	Accuracy	Date
DEMO-Net(weight)	DEMO-Net: Degree-specific Graph Neural Networks f…	64.70	2019-06-05
Planetoid*	Revisiting Semi-Supervised Learning with Graph Em…	64.70	2016-03-29
GAT (Velickovic et al., 2018)	Graph Attention Networks	58.50	2017-10-30
Union (Li et al., 2018)	Deeper Insights into Graph Convolutional Networks…	58.20	2018-01-22
Intersection (Li et al., 2018)	Deeper Insights into Graph Convolutional Networks…	57.30	2018-01-22
GraphSAGE (Hamilton et al., [2017a])	Inductive Representation Learning on Large Graphs	31.60	2017-06-07
UGT	Transitivity-Preserving Graph Representation Lear…		2023-08-18