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

主要结论

• 深度学习 · graph neural networks论文从 2023 年的 728 篇降到 2026 年的 326 篇，热度在回落。
• NeurIPS 是发深度学习 · graph neural networks论文最多的会议，2023–2026 年共 842 篇，占四个会议总量的 51%。
• 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 9 篇增至 2026 年的 20 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 5；同组增长最快的扩散模型是 4.1 倍，深度学习 · graph neural networks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 New Perspective on Target-Conditioned Structural Dynamics for Link Prediction in Dynamic Graphs
• ICML 2026A Graph Foundation Model with Cross-Modal Alignment and Modality-Aware Expert Fusion for Multi-Modal Graphs
• ICLR 2026Laplacian Kernelized Bandit
• CVPR 2026Gamba Mamba-based graph convolutional network with dynamic graph topology learning
• NeurIPS 2025Depth-Width Tradeoffs for Transformers on Graph Tasks
• ICML 2025A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
• ICLR 2025Factor Graph-based Interpretable Neural Networks
• CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
• NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
• ICML 2024A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
• ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
• CVPR 2024Learning Structure-from-Motion with Graph Attention Networks
• NeurIPS 2023[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
• ICML 2023A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
• ICLR 2023Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
• CVPR 2023An Actor-Centric Causality Graph for Asynchronous Temporal Inference in Group Activity
• NeurIPS 2026A Topological Encoder Decoder Framework for Temporal Graph Learning
• ICML 2026A Graphop Analysis of Graph Neural Networks on Sparse Graphs: Generalization and Universal Approximation
• ICLR 2026GTool: Graph Enhanced Tool Planning with Large Language Model
• CVPR 2026GSNR Graph Smooth Null-Space Representation for Inverse Problems

全部深度学习 · graph neural networks论文

共 50 篇，第 1 / 1 页

1. ICLR 2025Beyond Circuit Connections: A Non-Message Passing Graph Transformer Approach for Quantum Error Mitigation
2. ICLR 2025Beyond Random Masking: When Dropout meets Graph Convolutional Networks
3. ICLR 2025Bias Mitigation in Graph Diffusion Models
4. ICLR 2025Biologically Plausible Brain Graph Transformer
5. ICLR 2025BrainOOD: Out-of-distribution Generalizable Brain Network Analysis
6. ICLR 2025Centrality-guided Pre-training for Graph
7. ICLR 2025Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
8. ICLR 2025Deep Signature: Characterization of Large-Scale Molecular Dynamics
9. ICLR 2025Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing
10. ICLR 2025Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
11. ICLR 2025DUALFormer: Dual Graph Transformer
12. ICLR 2025Edge Prompt Tuning for Graph Neural Networks
13. ICLR 2025Energy-based Backdoor Defense Against Federated Graph Learning
14. ICLR 2025Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models
15. ICLR 2025Factor Graph-based Interpretable Neural Networks
16. ICLR 2025Generalizing Weisfeiler-Lehman Kernels to Subgraphs
17. ICLR 2025Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling
18. ICLR 2025Graph Neural Networks Can (Often) Count Substructures
19. ICLR 2025Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems
20. ICLR 2025Graph Transformers Dream of Electric Flow
21. ICLR 2025Graph-based Document Structure Analysis
22. ICLR 2025HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
23. ICLR 2025Homomorphism Counts as Structural Encodings for Graph Learning
24. ICLR 2025Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
25. ICLR 2025How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
26. ICLR 2025IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
27. ICLR 2025Improving Graph Neural Networks by Learning Continuous Edge Directions
28. ICLR 2025KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks
29. ICLR 2025Learning Graph Invariance by Harnessing Spuriosity
30. ICLR 2025Learning Graph Quantized Tokenizers
31. ICLR 2025Learning Partial Graph Matching via Optimal Partial Transport
32. ICLR 2025Learning system dynamics without forgetting
33. ICLR 2025MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
34. ICLR 2025On the Completeness of Invariant Geometric Deep Learning Models
35. ICLR 2025Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems
36. ICLR 2025PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph
37. ICLR 2025Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
38. ICLR 2025Precedence-Constrained Winter Value for Effective Graph Data Valuation
39. ICLR 2025Quality Measures for Dynamic Graph Generative Models
40. ICLR 2025REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring
41. ICLR 2025Recovery of Causal Graph Involving Latent Variables via Homologous Surrogates
42. ICLR 2025Rethinking Graph Neural Networks From A Geometric Perspective Of Node Features
43. ICLR 2025Scale-Free Graph-Language Models
44. ICLR 2025Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation
45. ICLR 2025SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs
46. ICLR 2025Spectro-Riemannian Graph Neural Networks
47. ICLR 2025Towards Continuous Reuse of Graph Models via Holistic Memory Diversification
48. ICLR 2025Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming
49. ICLR 2025Training One-Dimensional Graph Neural Networks is NP-Hard
50. ICLR 2025When Graph Neural Networks Meet Dynamic Mode Decomposition

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。