图神经网络论文趋势 2023–2026

主要结论

• 图神经网络论文从 2023 年的 434 篇降到 2026 年的 183 篇，热度在回落。
• NeurIPS 是发图神经网络论文最多的会议，2023–2026 年共 489 篇，占四个会议总量的 47%。
• 交叉方向里涨得最快的是数据集与基准：同时属于两个主题的论文从 2023 年的 10 篇增至 2026 年的 10 篇。
• 在「图与结构化数据」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的时间序列是 3.2 倍，图神经网络是 0.4 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• NeurIPS 2026A Differentiable 3D Scene Graph Metric via Contextual Hellinger Triplet Geometry
• ICML 2026Aitchison Embeddings for Learning Compositional Graph Representations
• ICLR 2026Certified Evaluation of Model-Level Explanations for Graph Neural Networks
• CVPR 2026Gamba Mamba-based graph convolutional network with dynamic graph topology learning
• NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
• ICML 2025Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts
• ICLR 2025Edge Prompt Tuning for Graph Neural Networks
• CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
• NeurIPS 2024[Re] Reproducibility Study of “Explaining Temporal Graph Models Through an Explorer-Navigator Framework"
• ICML 2024A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
• ICLR 2024Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
• CVPR 2024FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer
• NeurIPS 2023[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
• ICML 2023Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering
• ICLR 2023$\mathscr{N}$-WL: A New Hierarchy of Expressivity for Graph Neural Networks
• CVPR 2023Adversarially Robust Neural Architecture Search for Graph Neural Networks
• NeurIPS 2026A Topological Encoder Decoder Framework for Temporal Graph Learning
• ICML 2026Any-dimensional invariant universality
• ICLR 2026Laplacian Kernelized Bandit
• CVPR 2026Global-Aware Edge Prioritization for Pose Graph Initialization

全部图神经网络论文

共 45 篇，第 1 / 1 页

1. ICLR 2024A Topological Perspective on Demystifying GNN-Based Link Prediction Performance
2. ICLR 2024Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
3. ICLR 2024Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
4. ICLR 2024Clifford Group Equivariant Simplicial Message Passing Networks
5. ICLR 2024Conformal Inductive Graph Neural Networks
6. ICLR 2024CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs
7. ICLR 2024Counting Graph Substructures with Graph Neural Networks
8. ICLR 2024Effective Structural Encodings via Local Curvature Profiles
9. ICLR 2024Equivariant Matrix Function Neural Networks
10. ICLR 2024EX-Graph: A Pioneering Dataset Bridging Ethereum and X
11. ICLR 2024Forward Learning of Graph Neural Networks
12. ICLR 2024From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module
13. ICLR 2024G$^2$N$^2$ : Weisfeiler and Lehman go grammatical
14. ICLR 2024GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking
15. ICLR 2024GOAt: Explaining Graph Neural Networks via Graph Output Attribution
16. ICLR 2024Graph Lottery Ticket Automated
17. ICLR 2024Graph Metanetworks for Processing Diverse Neural Architectures
18. ICLR 2024Graph Neural Networks for Learning Equivariant Representations of Neural Networks
19. ICLR 2024Graph Parsing Networks
20. ICLR 2024GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks
21. ICLR 2024Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
22. ICLR 2024HiGen: Hierarchical Graph Generative Networks
23. ICLR 2024Hybrid Directional Graph Neural Network for Molecules
24. ICLR 2024Mirage: Model-agnostic Graph Distillation for Graph Classification
25. ICLR 2024MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy
26. ICLR 2024Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
27. ICLR 2024NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
28. ICLR 2024On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters
29. ICLR 2024Online GNN Evaluation Under Test-time Graph Distribution Shifts
30. ICLR 2024Orbit-Equivariant Graph Neural Networks
31. ICLR 2024Partitioning Message Passing for Graph Fraud Detection
32. ICLR 2024PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters
33. ICLR 2024Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
34. ICLR 2024PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
35. ICLR 2024Probabilistically Rewired Message-Passing Neural Networks
36. ICLR 2024Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
37. ICLR 2024Rethinking and Extending the Probabilistic Inference Capacity of GNNs
38. ICLR 2024Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
39. ICLR 2024Robust Angular Synchronization via Directed Graph Neural Networks
40. ICLR 2024SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
41. ICLR 2024TEDDY: Trimming Edges with Degree-based Discrimination Strategy
42. ICLR 2024Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
43. ICLR 2024Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND
44. ICLR 2024VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition
45. ICLR 2024VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections

常见问题

2023–2026 年四大会议一共有多少篇图神经网络论文？

共 1,038 篇，按年份分别是 2023 年 434 篇、2024 年 208 篇、2025 年 213 篇、2026 年 183 篇。

NeurIPS 2026 有多少篇图神经网络论文？

NeurIPS 2026 有 74 篇图神经网络论文，上一届是 75 篇。

ICLR 2026 有多少篇图神经网络论文？

ICLR 2026 有 28 篇图神经网络论文，上一届是 45 篇。

ICML 2026 有多少篇图神经网络论文？

ICML 2026 有 68 篇图神经网络论文，上一届是 81 篇。

CVPR 2026 有多少篇图神经网络论文？

CVPR 2026 有 13 篇图神经网络论文，上一届是 12 篇。

哪个会议的图神经网络论文最多？

NeurIPS，2023–2026 年共 489 篇。