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 533 篇，第 5 / 11 页

  1. ICML 2025Do We Really Need Message Passing in Brain Network Modeling?
  2. ICML 2025Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysis
  3. ICML 2025Dynamic Similarity Graph Construction with Kernel Density Estimation
  4. ICML 2025EAGLES: Towards Effective, Efficient, and Economical Federated Graph Learning via Unified Sparsification
  5. ICML 2025EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance Prediction
  6. ICML 2025Efficient Graph Continual Learning via Lightweight Graph Neural Tangent Kernels-based Dataset Distillation
  7. ICML 2025EmoGrowth: Incremental Multi-label Emotion Decoding with Augmented Emotional Relation Graph
  8. ICML 2025ENAHPool: The Edge-Node Attention-based Hierarchical Pooling for Graph Neural Networks
  9. ICML 2025Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of Invariance
  10. ICML 2025Enhancing Graph Invariant Learning from a Negative Inference Perspective
  11. ICML 2025Enhancing Spectral GNNs: From Topology and Perturbation Perspectives
  12. ICML 2025Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks
  13. ICML 2025Equivalence is All: A Unified View for Self-supervised Graph Learning
  14. ICML 2025EvoMesh: Adaptive Physical Simulation with Hierarchical Graph Evolutions
  15. ICML 2025Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs
  16. ICML 2025FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks
  17. ICML 2025From Theory to Practice: Rethinking Green and Martin Kernels for Unleashing Graph Transformers
  18. ICML 2025G-Adaptivity: optimised graph-based mesh relocation for finite element methods
  19. ICML 2025G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks
  20. ICML 2025GCAL: Adapting Graph Models to Evolving Domain Shifts
  21. ICML 2025Geometric Hyena Networks for Large-scale Equivariant Learning
  22. ICML 2025GPEN: Global Position Encoding Network for Enhanced Subgraph Representation Learning
  23. ICML 2025Graph Adaptive Autoregressive Moving Average Models
  24. ICML 2025Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models
  25. ICML 2025Graph Generative Pre-trained Transformer
  26. ICML 2025Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation
  27. ICML 2025Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning
  28. ICML 2025Graph-Based Algorithms for Diverse Similarity Search
  29. ICML 2025Graph4MM: Weaving Multimodal Learning with Structural Information
  30. ICML 2025GraphGPT: Generative Pre-trained Graph Eulerian Transformer
  31. ICML 2025Griffin: Towards a Graph-Centric Relational Database Foundation Model
  32. ICML 2025GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers
  33. ICML 2025Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks
  34. ICML 2025Hgformer: Hyperbolic Graph Transformer for Collaborative Filtering
  35. ICML 2025HGOT: Self-supervised Heterogeneous Graph Neural Network with Optimal Transport
  36. ICML 2025Hierarchical Graph Tokenization for Molecule-Language Alignment
  37. ICML 2025How Expressive are Knowledge Graph Foundation Models?
  38. ICML 2025How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
  39. ICML 2025Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations
  40. ICML 2025HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks
  41. ICML 2025Implicit degree bias in the link prediction task
  42. ICML 2025Implicit Subgraph Neural Network
  43. ICML 2025Improved Approximations for Hard Graph Problems using Predictions
  44. ICML 2025Improved Expressivity of Hypergraph Neural Networks through High-Dimensional Generalized Weisfeiler-Leman Algorithms
  45. ICML 2025Improving Soft Unification with Knowledge Graph Embedding Methods
  46. ICML 2025Improving the Effective Receptive Field of Message-Passing Neural Networks
  47. ICML 2025iN2V: Bringing Transductive Node Embeddings to Inductive Graphs
  48. ICML 2025Instance Correlation Graph-based Naive Bayes
  49. ICML 2025Large Language-Geometry Model: When LLM meets Equivariance
  50. ICML 2025Learn Beneficial Noise as Graph Augmentation

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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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