图神经网络论文趋势 2023–2026

GNN 架构

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,038 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

图神经网络论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023251699618434
20248945686208
202575458112213
202674286813183

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

全部图神经网络论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 1,038 篇，第 14 / 21 页

  1. ICLR 2023Explaining Temporal Graph Models through an Explorer-Navigator Framework
  2. ICLR 2023ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion
  3. ICLR 2023Fair Attribute Completion on Graph with Missing Attributes
  4. ICLR 2023FoSR: First-order spectral rewiring for addressing oversquashing in GNNs
  5. ICLR 2023Fundamental Limits in Formal Verification of Message-Passing Neural Networks
  6. ICLR 2023GNNDelete: A General Strategy for Unlearning in Graph Neural Networks
  7. ICLR 2023GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
  8. ICLR 2023Graph Domain Adaptation via Theory-Grounded Spectral Regularization
  9. ICLR 2023Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning
  10. ICLR 2023Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
  11. ICLR 2023Graph Neural Networks for Link Prediction with Subgraph Sketching
  12. ICLR 2023GReTo: Remedying dynamic graph topology-task discordance via target homophily
  13. ICLR 2023Grounding Graph Network Simulators using Physical Sensor Observations
  14. ICLR 2023Latent Graph Inference using Product Manifolds
  15. ICLR 2023Learnable Graph Convolutional Attention Networks
  16. ICLR 2023Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks
  17. ICLR 2023Learning Fair Graph Representations via Automated Data Augmentations
  18. ICLR 2023Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
  19. ICLR 2023Learning Hierarchical Protein Representations via Complete 3D Graph Networks
  20. ICLR 2023Learning rigid dynamics with face interaction graph networks
  21. ICLR 2023LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation
  22. ICLR 2023Limitless Stability for Graph Convolutional Networks
  23. ICLR 2023Matching receptor to odorant with protein language and graph neural networks
  24. ICLR 2023MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
  25. ICLR 2023Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules
  26. ICLR 2023NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
  27. ICLR 2023On Compositional Uncertainty Quantification for Seq2seq Graph Parsing
  28. ICLR 2023On Representing Linear Programs by Graph Neural Networks
  29. ICLR 2023On Representing Mixed-Integer Linear Programs by Graph Neural Networks
  30. ICLR 2023Re-parameterizing Your Optimizers rather than Architectures
  31. ICLR 2023Rethinking Graph Lottery Tickets: Graph Sparsity Matters
  32. ICLR 2023Rethinking the Expressive Power of GNNs via Graph Biconnectivity
  33. ICLR 2023REVISITING PRUNING AT INITIALIZATION THROUGH THE LENS OF RAMANUJAN GRAPH
  34. ICLR 2023Robust Graph Dictionary Learning
  35. ICLR 2023Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
  36. ICLR 2023Serving Graph Compression for Graph Neural Networks
  37. ICLR 2023Specformer: Spectral Graph Neural Networks Meet Transformers
  38. ICLR 2023Strategic Classification with Graph Neural Networks
  39. ICLR 2023Subsampling in Large Graphs Using Ricci Curvature
  40. ICLR 2023Towards Open Temporal Graph Neural Networks
  41. ICLR 2023Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States
  42. ICML 2023A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests
  43. ICML 2023A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel
  44. ICML 2023A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
  45. ICML 2023A Large-Scale Study of Probabilistic Calibration in Neural Network Regression
  46. ICML 2023Adaptive Smoothing Gradient Learning for Spiking Neural Networks
  47. ICML 2023All in a Row: Compressed Convolution Networks for Graphs
  48. ICML 2023Alternately Optimized Graph Neural Networks
  49. ICML 2023Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels
  50. ICML 2023Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查图神经网络在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？

AI 会调用的工具：get_topic_stats {"topic": "graph-neural-networks-topic"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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