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 18 / 21 页

  1. NeurIPS 2023Efficient Learning of Linear Graph Neural Networks via Node Subsampling
  2. NeurIPS 2023Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks
  3. NeurIPS 2023Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity
  4. NeurIPS 2023Empowering Convolutional Neural Nets with MetaSin Activation
  5. NeurIPS 2023Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks
  6. NeurIPS 2023Enhancing Sharpness-Aware Optimization Through Variance Suppression
  7. NeurIPS 2023Entropic Neural Optimal Transport via Diffusion Processes
  8. NeurIPS 2023Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs
  9. NeurIPS 2023Equivariant Neural Operator Learning with Graphon Convolution
  10. NeurIPS 2023Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics
  11. NeurIPS 2023Euler-Lagrange Analysis of Generative Adversarial Networks
  12. NeurIPS 2023Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
  13. NeurIPS 2023Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis
  14. NeurIPS 2023Evolving Connectivity for Recurrent Spiking Neural Networks
  15. NeurIPS 2023Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings
  16. NeurIPS 2023Exact Verification of ReLU Neural Control Barrier Functions
  17. NeurIPS 2023Explainable Brain Age Prediction using coVariance Neural Networks
  18. NeurIPS 2023Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks
  19. NeurIPS 2023Expressive probabilistic sampling in recurrent neural networks
  20. NeurIPS 2023Expressive Sign Equivariant Networks for Spectral Geometric Learning
  21. NeurIPS 2023Expressivity-Preserving GNN Simulation
  22. NeurIPS 2023Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman
  23. NeurIPS 2023Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes
  24. NeurIPS 2023Fair Graph Distillation
  25. NeurIPS 2023FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks
  26. NeurIPS 2023Fine-grained Expressivity of Graph Neural Networks
  27. NeurIPS 2023Flat Seeking Bayesian Neural Networks
  28. NeurIPS 2023FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
  29. NeurIPS 2023From Tempered to Benign Overfitting in ReLU Neural Networks
  30. NeurIPS 2023Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
  31. NeurIPS 2023Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks
  32. NeurIPS 2023Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications
  33. NeurIPS 2023GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
  34. NeurIPS 2023Generalised f-Mean Aggregation for Graph Neural Networks
  35. NeurIPS 2023Generalization bounds for neural ordinary differential equations and deep residual networks
  36. NeurIPS 2023GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising
  37. NeurIPS 2023GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels
  38. NeurIPS 2023Going beyond persistent homology using persistent homology
  39. NeurIPS 2023GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks
  40. NeurIPS 2023Graph Clustering with Graph Neural Networks
  41. NeurIPS 2023Graph Convolutional Kernel Machine versus Graph Convolutional Networks
  42. NeurIPS 2023Graph Denoising Diffusion for Inverse Protein Folding
  43. NeurIPS 2023Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
  44. NeurIPS 2023Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis
  45. NeurIPS 2023Graph of Circuits with GNN for Exploring the Optimal Design Space
  46. NeurIPS 2023GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search
  47. NeurIPS 2023GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation
  48. NeurIPS 2023GSLB: The Graph Structure Learning Benchmark
  49. NeurIPS 2023Hierarchical Randomized Smoothing
  50. NeurIPS 2023HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation

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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