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Awesome graph-level learning methods. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in graph repr...

Awesome Graph Level Learning

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A collection of papers, implementations, datasets, and tools for graph-level learning.

  • Awesome Graph-level Learning
    • Surveys
    • Traditional Graph-level Learning
      • Graph Kernels
        • Message Passing Kernels
        • Shortest Path Kernels
        • Random Walk Kernels
        • Optimal Assignment Kernels
        • Subgraph Kernels
      • Subgraph Mining
        • Frequent Subgraph Mining
        • Discriminative Subgraph Mining
      • Graph Embedding
        • Deterministic Graph Embedding
        • Learnable Graph Embedding
    • Graph-Level Deep Neural Networks (GL-DNNs)
      • Recurrent Neural Network-based Graph-level Learning
      • Convolution Neural Network-based Graph-level Learning
      • Capsule Neural Network-based Graph-level Learning
    • Graph-Level Graph Neural Networks (GL-GNNs)
      • Message Passing Neural Networks
      • Subgraph-based GL-GNNs
      • Kernel-based GL-GNNs
      • Contrastive-based GL-GNNs
      • Spectral-based GL-GNNs
    • Graph Pooling
      • Global Graph Pooling
        • Numeric Operation Pooling
        • Attention-based Pooling
        • Convolution Neural Network-based Pooling
        • Global Top-K Pooling
      • Hierarchical Graph Pooling
        • Clustering-based Pooling
        • Hierarchical Top-K Pooling
        • Hierarchical Tree-based Pooling
    • Datasets
    • Tools

A Timeline of Graph-level Learning

timeline

Surveys

Paper Title Venue Year Materials
A Comprehensive Survey of Graph-level Learning arXiv 2023 [Paper]
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities arXiv 2022 [Paper]
Graph-level Neural Networks: Current Progress and Future Directions arXiv 2022 [Paper]
A Survey on Graph Kernels Appl. Netw. Sci. 2020 [Paper]
Deep Learning on Graphs: A Survey IEEE Trans. Knowl. Data Eng. 2020 [Paper]
A Comprehensive Survey on Graph Neural Networks IEEE Trans. Neural Netw. Learn. Syst. 2020 [Paper]

Traditional Graph-level Learning

Graph Kernels

Message Passing Kernels

Paper Title Venue Year Method Materials
A Persistent Weisfeiler-lehman Procedure for Graph Classification ICML 2019 P-WL [Paper] [Code]
Glocalized Weisfeiler-lehman Graph Kernels: Global-local Feature Maps of Graphs ICDM 2017 Global-WL [Paper] [Code]
Propagation kernels: Efficient Graph Kernels from Propagated Information Mach. Learn. 2016 PK [Paper] [Code]
Weisfeiler-lehman Graph Kernels J. Mach. Learn. Res. 2011 WL [Paper] [Code]
A linear-time graph kernel ICDM 2009 NHK [Paper] [Code]

Shortest Path Kernels

Paper Title Venue Year Method Materials
Shortest-path Graph Kernels for Document Similarity EMNLP 2017 SPK-DS [Paper]
Shortest-path Kernels on Graphs ICDM 2005 SPK [Paper] [Code]

Random Walk Kernels

Paper Title Venue Year Method Materials
Graph Kernels J. Mach. Learn. Res. 2010 SOMRWK [Paper] [Code]
Extensions of Marginalized Graph Kernels ICML 2004 ERWK [Paper] [Code]
On Graph Kernels: Hardness Results and Efficient Alternatives LNAI 2003 RWK [Paper] [Code]

Optimal Assignment Kernels

Paper Title Venue Year Method Materials
Transitive Assignment Kernels for Structural Classification SIMBAD 2015 TAK [Paper]
Learning With Similarity Functions on Graphs Using Matchings of Geometric Embeddings KDD 2015 GE-OAK [Paper]
Solving the Multi-way Matching Problem by Permutation Synchronization NeurIPS 2013 PS-OAK [Paper] [Code]
Optimal Assignment Kernels for Attributed Molecular Graphs ICML 2005 OAK [Paper]

Subgraph Kernels

Paper Title Venue Year Method Materials
Subgraph Matching Kernels for Attributed Graphs ICML 2012 SMK [Paper] [Code]
Fast Neighborhood Subgraph Pairwise Distance Kernel ICML 2010 NSPDK [Paper] [Code]
Efficient Graphlet Kernels for Large Graph Comparison AISTATS 2009 Graphlet [Paper] [Code]

Subgraph Mining

Frequent Subgraph Mining

Paper Title Venue Year Method Materials
gspan: Graph-based Substructure Pattern Mining ICDM 2002 gspan [Paper] [Code]
Frequent Subgraph Discovery ICDM 2001 FSG [Paper] [Code]
An Apriori-based Algorithmfor Mining Frequent Substructures from Graph Data ECML-PKDD 2000 AGM [Paper] [Code]

Discriminative Subgraph Mining

Paper Title Venue Year Method Materials
Multi-graph-view Learning for Graph Classification ICDM 2014 gCGVFL [Paper]
Positive and Unlabeled Learning for Graph Classification ICDM 2011 gPU [Paper]
Semi-supervised Feature Selection for Graph Classification KDD 2010 gSSC [Paper]
Multi-label Feature Selection for Graph Classification ICDM 2010 gMLC [Paper]
Near-optimal Supervised Feature Selection Among Frequent Subgraphs SDM 2009 CORK [Paper]
Mining Significant Graph Patterns by Leap Search SIGMOD 2008 LEAP [Paper]

Graph Embedding

Deterministic Graph Embedding

Paper Title Venue Year Method Materials
Fast Attributed Graph Embedding via Density of States ICDM 2021 A-DOGE [Paper] [Code]
Bridging the Gap Between Von Neumann Graph Entropy and Structural Information: Theory and Applications WWW 2021 VNGE [Paper] [Code]
Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs WWW 2021 SLAQ [Paper] [Code]
A Simple Yet Effective Baseline for Non-attributed Graph Classification ICLR-RLGM 2019 LDP [Paper] [Code]
Anonymous Walk Embeddings ICML 2018 AWE [Paper] [Code]
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs NeurIPS 2017 FGSD [Paper] [Code]

Learnable Graph Embedding

Paper Title Venue Year Method Materials
Learning Graph Representation via Frequent Subgraphs SDM 2018 GE-FSG [Paper] [Code]
graph2vec: Learning Distributed Representations of Graphs KDD-MLG 2017 graph2vec [Paper] [Code]
subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs KDD-MLG 2016 subgraph2vec [Paper] [Code]

Graph-Level Deep Neural Networks

Recurrent Neural Network-based Graph-level Learning

Paper Title Venue Year Method Materials
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models ICML 2018 GraphRNN [Paper] [Code]
NetGAN: Generating Graphs via Random Walks ICML 2018 NetGAN [Paper] [Code]
Substructure Assembling Network for Graph Classification AAAI 2018 SAN [Paper]
Graph Classification using Structural Attention KDD 2018 GAM [Paper] [Code]
Gated Graph Sequence Neural Networks ICLR 2016 GGNN [Paper] [Code]

Convolution Neural Network-based Graph-level Learning

Paper Title Venue Year Method Materials
Kernel Graph Convolutional Neural Networks ICANN 2018 KCNN [Paper] [Code]
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs CVPR 2017 ECC [Paper] [Code]
Diffusion-Convolutional Neural Networks NeurIPS 2016 DCNN [Paper] [Code]
Learning Convolutional Neural Networks for Graphs ICML 2016 PATCHYSAN [Paper] [Code]

Capsule Neural Network-based Graph-level Learning

Paper Title Venue Year Method Materials
Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations arXiv 2019 PATCHYCaps [Paper] [Code]
Capsule Graph Neural Network ICLR 2019 CapsGNN [Paper] [Code]
Graph Capsule Convolutional Neural Networks WCB 2018 GCAPSCNN [Paper] [Code]

Graph-Level Graph Neural Networks

Message Passing Neural Networks

Paper Title Venue Year Method Materials
The Surprising Power of Graph Neural Networks with Random Node Initialization IJCAI 2021 RNI [Paper]
Weisfeiler and Lehman Go Cellular: CW Networks NeurIPS 2021 CWN [Paper] [Code]
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks ICML 2021 SWL [Paper] [Code]
Expressive Power of Invariant and Equivariant Graph Neural Networks ICLR 2021 FGNN [Paper] [Code]
Relational Pooling for Graph Representations ICML 2019 RP [Paper] [Code]
Provably Powerful Graph Networks NeurIPS 2019 PPGN [Paper] [Code]
Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks AAAI 2019 K-GNN [Paper] [Code]
How Powerful are Graph Neural Networks? ICLR 2019 GIN [Paper] [Code]
Quantum-chemical Insights from Deep Tensor Neural Networks Nat. Commun. 2017 DTNN [Paper] [Code]
Neural Message Passing for Quantum Chemistry ICML 2017 MPNN [Paper] [Code]
Interaction Networks for Learning about Objects, Relations and Physics NeurIPS 2016 GraphSim [Paper] [Code]
Convolutional Networks on Graphs for Learning Molecular Fingerprints NeurIPS 2015 Fingerprint [Paper] [Code]

Subgraph-based GL-GNNs

Paper Title Venue Year Method Materials
Equivariant Subgraph Aggregation Networks ICLR 2021 ESAN [Paper] [Code]
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism WWW 2021 SUGAR [Paper] [Code]
A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?" ICLR 2021 GraphSNN [Paper] [Code]
Nested Graph Neural Network NeurIPS 2021 NGNN [Paper] [Code]
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness ICLR 2021 GNN-AK [Paper] [Code]
Subgraph Neural Networks NeurIPS 2020 SubGNN [Paper] [Code]
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting IEEE Trans. Pattern Anal. Mach. Intell. 2020 GSN [Paper] [Code]

Kernel-based GL-GNNs

Paper Title Venue Year Method Materials
Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels WWW 2021 GSKN [Paper] [Code]
Random Walk Graph Neural Networks NeurIPS 2020 RWNN [Paper] [Code]
Convolutional Kernel Networks for Graph-Structured Data ICML 2020 GCKN [Paper] [Code]
DDGK: Learning Graph Representations for Deep Divergence Graph Kernels WWW 2019 DDGK [Paper] [Code]
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels NeurIPS 2019 GNTK [Paper] [Code]

Contrastive-based GL-GNNs

Paper Title Venue Year Method Materials
Graph Contrastive Learning Automated ICML 2021 JOAO [Paper] [Code]
Contrastive Multi-View Representation Learning on Graphs ICML 2020 MVGRL [Paper] [Code]
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training KDD 2020 ESAN [Paper] [Code]
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization ICLR 2020 InfoGraph [Paper] [Code]
Graph Contrastive Learning with Augmentations NeurIPS 2020 GraphCL [Paper] [Code]

Spectral-based GL-GNNs

Paper Title Venue Year Method Materials
How Framelets Enhance Graph Neural Networks ICML 2021 UFG [Paper] [Code]
Graph Neural Networks With Convolutional ARMA Filters IEEE Trans. Pattern Anal. Mach. Intell. 2021 ARMA [Paper] [Code]
Breaking the Limits of Message Passing Graph Neural Networks ICML 2021 GNNMatlang [Paper] [Code]
Transferability of Spectral Graph Convolutional Neural Networks J. Mach. Learn. Res. 2021 GNNTFS [Paper]
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering NeurIPS 2016 ChebNet [Paper] [Code]

Graph Pooling

Global Graph Pooling

Numeric Operation Pooling

Paper Title Venue Year Method Materials
Second-Order Pooling for Graph Neural Networks IEEE Trans. Pattern Anal. Mach. Intell 2020 SOPOOL [Paper] [Code]
Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks ACL 2020 TextING [Paper] [Code]
Principal Neighbourhood Aggregation for Graph Nets NeurIPS 2020 PNA [Paper] [Code]

Attention-based Pooling

Paper Title Venue Year Method Materials
Order Matters: Sequence to Sequence for Sets ICLR 2021 Set2Set [Paper] [Code]

Convolution Neural Network-based Pooling

Paper Title Venue Year Method Materials
Kernel Graph Convolutional Neural Networks ICANN 2018 KCNN [Paper] [Code]
Learning Convolutional Neural Networks for Graphs ICML 2016 PATCHYSAN [Paper] [Code]

Global Top-K Pooling

Paper Title Venue Year Method Materials
Structure-Feature based Graph Self-adaptive Pooling WWW 2020 GSAPool [Paper] [Code]
An End-to-End Deep Learning Architecture for Graph Classification AAAI 2018 SortPool [Paper] [Code]

Hierarchical Graph Pooling

Clustering-based Pooling

Paper Title Venue Year Method Materials
Accurate Learning of Graph Representations with Graph Multiset Pooling ICLR 2020 GMT [Paper] [Code]
Spectral Clustering with Graph Neural Networks for Graph Pooling ICML 2020 MinCutPool [Paper] [Code]
StructPool: Structured Graph Pooling via Conditional Random Fields ICLR 2020 StructPool [Paper] [Code]
Graph Convolutional Networks with EigenPooling KDD 2019 EigenPool [Paper] [Code]
Hierarchical Graph Representation Learning with Differentiable Pooling NeurIPS 2018 DiffPool [Paper] [Code]
Deep Convolutional Networks on Graph-Structured Data arXiv 2015 GraphCNN [Paper] [Code]
Spectral Networks and Locally Connected Networks on Graphs ICLR 2014 DLCN [Paper]

Hierarchical Top-K Pooling

Paper Title Venue Year Method Materials
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations AAAI 2020 ASAP [Paper] [Code]
Self-Attention Graph Pooling ICML 2019 SAGPool [Paper] [Code]
Graph U-Nets ICML 2019 U-Nets [Paper] [Code]
Towards Sparse Hierarchical Graph Classifiers arXiv 2018 SHGC [Paper] [Code]

Hierarchical Tree-based Pooling

Paper Title Venue Year Method Materials
A Simple yet Effective Method for Graph Classification IJCAI 2022 HRN [Paper] [Code]
Edge Contraction Pooling for Graph Neural Networks arXiv 2019 EdgePool [Paper] [Code]
Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs CVPR 2017 MoNet [Paper] [Code]

Datasets

Biology

Dataset Size Graphs Classes Link
ENZYMES Small 600 6 Link
PROTEINS Small 1113 2 Link
D&D Small 1178 2 Link
BACE Small 1513 2 Link
MUV Medium 93087 2 Link
ppa Medium 158100 37 Link

Chemistry

Dataset Size Graphs Classes Link
MUTAG Small 188 2 Link
SIDER Small 1427 2 Link
ClinTox Small 1477 2 Link
BBBP Small 2039 2 Link
Tox21 Small 7831 2 Link
ToxCast Small 8576 2 Link
molhiv Small 41127 2 Link
molpcba Medium 437929 2 Link
FreeSolv Small 642 - Link
ESOL Small 1128 - Link
Lipophilicity Small 4200 - Link
AQSOL Small 9823 - Link
ZINC Small 12000 - Link
QM9 Medium 129433 - Link

Social Networks

Dataset Size Graphs Classes Link
IMDB-BINARY Small 1000 2 Link
IMDB-MULTI Small 1500 3 Link
DBLP_v1 Small 19456 2 Link
COLLAB Medium 5000 3 Link
REDDIT-BINARY Small 2000 2 Link
REDDIT-MULTI-5K Medium 4999 5 Link
REDDIT-MULTI-12K Medium 11929 11 Link

Computer Science

Dataset Size Graphs Classes Link
CIFAR10 Medium 60000 10 Link
MNIST Medium 70000 10 Link
code2 Medium 452741 - Link
MALNET Large 1262024 696 Link

Dataset Library

  • TUDataset https://chrsmrrs.github.io/datasets/docs/datasets/
  • MoleculeNetDataset https://moleculenet.org/datasets-1
  • OGBDataset https://ogb.stanford.edu/docs/graphprop/
  • BenchmarkingDataset https://github.com/graphdeeplearning/benchmarking-gnns

Tools

  • DGL https://www.dgl.ai/
  • Geometric https://pytorch-geometric.readthedocs.io/en/latest/
  • OGB https://ogb.stanford.edu/docs/home/
  • Benchmarking https://github.com/graphdeeplearning/benchmarking-gnns

Disclaimer

If you have any questions, please feel free to contact us. Emails: [email protected], [email protected], [email protected]

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Awesome graph-level learning methods. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in graph repr...

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