Graph algorithms and clustering: research map
817 accepted papers on Graph algorithms and clustering in Graph learning, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 3 clusters and 9 approaches. The busiest year so far is 2026.
Within Graph learning, its share shrank from 15.4% in 2023–24 to 12.8% in 2025–26 (196 → 201 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).
Explore Graph algorithms and clustering in the interactive map
Working on something in this topic? Describe your idea in scime atlas to see which approach it falls under, the closest papers by meaning and how crowded the spot has become.
Approaches and key papers
search · directed · causal · 621 papers
Approaches in this cluster:
- Neural combinatorial optimization on graphs (159 papers)
Guide combinatorial and integer-programming solvers with graph neural networks. - Graph comparison and random features (155 papers)
Compare graphs with optimal transport and efficient graph random features. - Graph embedding and spectral sparsification (126 papers)
Scale graph embeddings via coarsening and spectral sparsification. - Continuous DAG structure learning (102 papers)
Learn DAG structure via continuous optimization and active experimental design. - Graph distance and retrieval (79 papers)
Learn graph edit distance and similarity for graph retrieval and coarsening.
Most cited and most cited since 2024:
- Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering (NeurIPS 2016 · 1,699 citations)
- Learning Combinatorial Optimization Algorithms over Graphs (NeurIPS 2017 · 1,066 citations)
- Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks (AAAI 2024 · 21 citations)
- Large-Scale Multi-Robot Coverage Path Planning via Local Search (AAAI 2024 · 14 citations)
graph clustering · spectral clustering · clusters · 112 papers
Approaches in this cluster:
- Neural and local graph clustering (81 papers)
Cluster graphs with neural modularity, flow diffusion, and correlation clustering. - Anchor-based multi-view clustering (31 papers)
Scale multi-view clustering with anchor graphs and alignment.
Most cited and most cited since 2024:
- Efficient One-Pass Multi-View Subspace Clustering with Consensus Anchors (AAAI 2022 · 206 citations)
- Linkage Based Face Clustering via Graph Convolution Network (CVPR 2019 · 201 citations)
- Attribute-Missing Graph Clustering Network (AAAI 2024 · 58 citations)
- DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization (AAAI 2024 · 32 citations)
graph matching · matching graph · correspondence · 84 papers
Approaches in this cluster:
- Deep learning for graph matching (42 papers)
Learn graph matching with neural networks and combinatorial solvers. - Optimization algorithms for graph matching (42 papers)
Solve graph matching with convex relaxations, dual decomposition, and update algorithms.
Most cited and most cited since 2024:
- Graph Matching Networks for Learning the Similarity of Graph Structured Objects (ICML 2019 · 298 citations)
- Deep Learning of Graph Matching (CVPR 2018 · 237 citations)
- Efficient Graph Matching for Correlated Stochastic Block Models (NeurIPS 2024 · 3 citations)
- Discrete Cycle-Consistency Based Unsupervised Deep Graph Matching (AAAI 2024 · 2 citations)
Related topics in Graph learning
- Knowledge and temporal graphs (974)
- GNN architectures (1,471)
- Graph self-supervised learning (1,274)