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
- 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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 489 | 68 | 148 | 23 | 728 |
| 2024 | 160 | 51 | 76 | 10 | 297 |
| 2025 | 91 | 50 | 141 | 15 | 297 |
| 2026 | 102 | 32 | 168 | 24 | 326 |
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 1,648 篇，第 11 / 33 页
- ICML 2025SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion
- ICML 2025Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation
- ICML 2025Scalable Sobolev IPM for Probability Measures on a Graph
- ICML 2025SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
- ICML 2025SHARP-Distill: A 68× Faster Recommender System with Hypergraph Neural Networks and Language Models
- ICML 2025Signed Laplacians for Constrained Graph Clustering
- ICML 2025Simple Path Structural Encoding for Graph Transformers
- ICML 2025Smooth Interpolation for Improved Discrete Graph Generative Models
- ICML 2025SPHINX: Structural Prediction using Hypergraph Inference Network
- ICML 2025Stability and Generalization Capability of Subgraph Reasoning Models for Inductive Knowledge Graph Completion
- ICML 2025Stable Fair Graph Representation Learning with Lipschitz Constraint
- ICML 2025Structure Is All You Need: Structural Representation Learning on Hyper-Relational Knowledge Graphs
- ICML 2025Supercharging Graph Transformers with Advective Diffusion
- ICML 2025Telling Peer Direct Effects from Indirect Effects in Observational Network Data
- ICML 2025Test-Time Graph Neural Dataset Search With Generative Projection
- ICML 2025The Generalized Skew Spectrum of Graphs
- ICML 2025The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products
- ICML 2025Thickness-aware E(3)-Equivariant 3D Mesh Neural Networks
- ICML 2025TMetaNet: Topological Meta-Learning Framework for Dynamic Link Prediction
- ICML 2025TopInG: Topologically Interpretable Graph Learning via Persistent Rationale Filtration
- ICML 2025Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph
- ICML 2025TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks
- ICML 2025Toward Data-centric Directed Graph Learning: An Entropy-driven Approach
- ICML 2025Towards characterizing the value of edge embeddings in Graph Neural Networks
- ICML 2025Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
- ICML 2025Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
- ICML 2025Vision Graph Prompting via Semantic Low-Rank Decomposition
- ICML 2025Weisfeiler and Leman Go Gambling: Why Expressive Lottery Tickets Win
- ICML 2025What Makes a Good Feedforward Computational Graph?
- ICML 2025When Do LLMs Help With Node Classification? A Comprehensive Analysis
- ICML 2025WILTing Trees: Interpreting the Distance Between MPNN Embeddings
- ICML 2025Zero-Shot Generalization of GNNs over Distinct Attribute Domains
- NeurIPS 20253D-GSRD: 3D Molecular Graph Auto-Encoder with Selective Re-mask Decoding
- NeurIPS 2025A Little Depth Goes a Long Way: The Expressive Power of Log-Depth Transformers
- NeurIPS 2025Adjusted Count Quantification Learning on Graphs
- NeurIPS 2025An Efficient Orlicz-Sobolev Approach for Transporting Unbalanced Measures on a Graph
- NeurIPS 2025Association-Focused Path Aggregation for Graph Fraud Detection
- NeurIPS 2025Coloring Learning for Heterophilic Graph Representation
- NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
- NeurIPS 2025DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases
- NeurIPS 2025Depth-Width Tradeoffs for Transformers on Graph Tasks
- NeurIPS 2025DGCBench: A Deep Graph Clustering Benchmark
- NeurIPS 2025DiffLiG: Diffusion-enhanced Liquid Graph with Attention Propagation for Grid-to-Station Precipitation Correction
- NeurIPS 2025Diffusion-Guided Graph Data Augmentation
- NeurIPS 2025Distribution Learning Meets Graph Structure Sampling
- NeurIPS 2025DualEqui: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules
- NeurIPS 2025Dynamic Configuration for Cutting Plane Separators via Reinforcement Learning on Incremental Graph
- NeurIPS 2025Effects of Dropout on Performance in Long-range Graph Learning Tasks
- NeurIPS 2025Enforcing convex constraints in Graph Neural Networks
- NeurIPS 2025Enhancing Graph Classification Robustness with Singular Pooling
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"}
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。
「深度学习」下的其他主题
- 扩散模型 6,900
- 深度学习 · generative models and autoencoders 4,314
- 深度学习 · large language models 2,334
- 深度学习 · self supervised learning 1,958
- 深度学习 · optimization 953
- 深度学习 · representation learning 802
- 深度学习 · probabilistic methods 637
- 深度学习 · foundation models 536
- 深度学习 · causal inference 316
- 深度学习 · transfer learning 197