深度学习 · graph neural networks论文趋势 2023–2026

ICML/NeurIPS 深度学习方向：graph_neural_networks

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,648 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

深度学习 · graph neural networks论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
20234896814823728
2024160517610297
2025915014115297
20261023216824326

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

全部深度学习 · graph neural networks论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 1,648 篇，第 16 / 33 页

  1. ICML 2024Simulation of Graph Algorithms with Looped Transformers
  2. ICML 2024SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter
  3. ICML 2024Structure Your Data: Towards Semantic Graph Counterfactuals
  4. ICML 2024Surprisingly Strong Performance Prediction with Neural Graph Features
  5. ICML 2024The Expressive Power of Path-Based Graph Neural Networks
  6. ICML 2024Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers
  7. ICML 2024Understanding Heterophily for Graph Neural Networks
  8. ICML 2024Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning
  9. ICML 2024Unsupervised Episode Generation for Graph Meta-learning
  10. ICML 2024VisionGraph: Leveraging Large Multimodal Models for Graph Theory Problems in Visual Context
  11. NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
  12. NeurIPS 2024[Re] Reproducibility Study of “Explaining Temporal Graph Models Through an Explorer-Navigator Framework"
  13. NeurIPS 2024A Canonicalization Perspective on Invariant and Equivariant Learning
  14. NeurIPS 2024A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening
  15. NeurIPS 2024A Foundation Model for Zero-shot Logical Query Reasoning
  16. NeurIPS 2024A Motion-aware Spatio-temporal Graph for Video Salient Object Ranking
  17. NeurIPS 2024A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning
  18. NeurIPS 2024A Topology-aware Graph Coarsening Framework for Continual Graph Learning
  19. NeurIPS 2024Accelerating Non-Maximum Suppression: A Graph Theory Perspective
  20. NeurIPS 2024Almost Surely Asymptotically Constant Graph Neural Networks
  21. NeurIPS 2024An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning
  22. NeurIPS 2024An End-To-End Graph Attention Network Hashing for Cross-Modal Retrieval
  23. NeurIPS 2024Analysis of Corrected Graph Convolutions
  24. NeurIPS 2024Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss
  25. NeurIPS 2024ARC: A Generalist Graph Anomaly Detector with In-Context Learning
  26. NeurIPS 2024Are Graph Neural Networks Optimal Approximation Algorithms?
  27. NeurIPS 2024Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?
  28. NeurIPS 2024Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections
  29. NeurIPS 2024Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning
  30. NeurIPS 2024Boosting Graph Pooling with Persistent Homology
  31. NeurIPS 2024Can Graph Learning Improve Planning in LLM-based Agents?
  32. NeurIPS 2024Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach
  33. NeurIPS 2024Challenges of Generating Structurally Diverse Graphs
  34. NeurIPS 2024Cluster-wise Graph Transformer with Dual-granularity Kernelized Attention
  35. NeurIPS 2024Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding
  36. NeurIPS 2024Continuous Partitioning for Graph-Based Semi-Supervised Learning
  37. NeurIPS 2024Continuous Product Graph Neural Networks
  38. NeurIPS 2024DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach
  39. NeurIPS 2024Deep Equilibrium Algorithmic Reasoning
  40. NeurIPS 2024Deep Graph Mating
  41. NeurIPS 2024Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module
  42. NeurIPS 2024Deep Homomorphism Networks
  43. NeurIPS 2024DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment
  44. NeurIPS 2024DiGRAF: Diffeomorphic Graph-Adaptive Activation Function
  45. NeurIPS 2024DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis
  46. NeurIPS 2024Dissecting the Failure of Invariant Learning on Graphs
  47. NeurIPS 2024Distributed-Order Fractional Graph Operating Network
  48. NeurIPS 2024DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks
  49. NeurIPS 2024Dynamic Rescaling for Training GNNs
  50. NeurIPS 2024Efficient Graph Matching for Correlated Stochastic Block Models

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用 paperlist 查深度学习 · graph neural networks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": "dl-graph-neural-networks"}

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常见问题

2023–2026 年四大会议一共有多少篇深度学习 · graph neural networks论文？
共 1,648 篇，按年份分别是 2023 年 728 篇、2024 年 297 篇、2025 年 297 篇、2026 年 326 篇。
NeurIPS 2026 有多少篇深度学习 · graph neural networks论文？
NeurIPS 2026 有 102 篇深度学习 · graph neural networks论文，上一届是 91 篇。
ICLR 2026 有多少篇深度学习 · graph neural networks论文？
ICLR 2026 有 32 篇深度学习 · graph neural networks论文，上一届是 50 篇。
ICML 2026 有多少篇深度学习 · graph neural networks论文？
ICML 2026 有 168 篇深度学习 · graph neural networks论文，上一届是 141 篇。
CVPR 2026 有多少篇深度学习 · graph neural networks论文？
CVPR 2026 有 24 篇深度学习 · graph neural networks论文，上一届是 15 篇。
哪个会议的深度学习 · graph neural networks论文最多？
NeurIPS，2023–2026 年共 842 篇。

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