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
- 图神经网络论文从 2023 年的 434 篇降到 2026 年的 183 篇,热度在回落。
- NeurIPS 是发图神经网络论文最多的会议,2023–2026 年共 489 篇,占四个会议总量的 47%。
- 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 10 篇增至 2026 年的 10 篇。
- 在「图与结构化数据」的 5 个主题里,它的 2026 年论文数排第 4;同组增长最快的时间序列是 3.2 倍,图神经网络是 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 | 251 | 69 | 96 | 18 | 434 |
| 2024 | 89 | 45 | 68 | 6 | 208 |
| 2025 | 75 | 45 | 81 | 12 | 213 |
| 2026 | 74 | 28 | 68 | 13 | 183 |
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 Differentiable 3D Scene Graph Metric via Contextual Hellinger Triplet Geometry
- ICML 2026Aitchison Embeddings for Learning Compositional Graph Representations
- ICLR 2026Certified Evaluation of Model-Level Explanations for Graph Neural Networks
- CVPR 2026Gamba Mamba-based graph convolutional network with dynamic graph topology learning
- NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
- ICML 2025Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts
- ICLR 2025Edge Prompt Tuning for Graph Neural Networks
- CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
- NeurIPS 2024[Re] Reproducibility Study of “Explaining Temporal Graph Models Through an Explorer-Navigator Framework"
- ICML 2024A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
- ICLR 2024Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
- CVPR 2024FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer
- NeurIPS 2023[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
- ICML 2023Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering
- ICLR 2023$\mathscr{N}$-WL: A New Hierarchy of Expressivity for Graph Neural Networks
- CVPR 2023Adversarially Robust Neural Architecture Search for Graph Neural Networks
- NeurIPS 2026A Topological Encoder Decoder Framework for Temporal Graph Learning
- ICML 2026Any-dimensional invariant universality
- ICLR 2026Laplacian Kernelized Bandit
- CVPR 2026Global-Aware Edge Prioritization for Pose Graph Initialization
全部图神经网络论文
共 434 篇,第 7 / 9 页
- NeurIPS 2023Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings
- NeurIPS 2023Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
- NeurIPS 2023Individualized Dosing Dynamics via Neural Eigen Decomposition
- NeurIPS 2023Information Geometry of the Retinal Representation Manifold
- NeurIPS 2023Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks
- NeurIPS 2023Inner Product-based Neural Network Similarity
- NeurIPS 2023Interpretable Graph Networks Formulate Universal Algebra Conjectures
- NeurIPS 2023Interpretable Prototype-based Graph Information Bottleneck
- NeurIPS 2023Investigating how ReLU-networks encode symmetries
- NeurIPS 2023Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
- NeurIPS 2023LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
- NeurIPS 2023Language Semantic Graph Guided Data-Efficient Learning
- NeurIPS 2023Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
- NeurIPS 2023Large sample spectral analysis of graph-based multi-manifold clustering
- NeurIPS 2023Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
- NeurIPS 2023Latent Graph Inference with Limited Supervision
- NeurIPS 2023Layer-Neighbor Sampling --- Defusing Neighborhood Explosion in GNNs
- NeurIPS 2023LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
- NeurIPS 2023Learning DAGs from Data with Few Root Causes
- NeurIPS 2023Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
- NeurIPS 2023Learning Invariant Representations of Graph Neural Networks via Cluster Generalization
- NeurIPS 2023Learning Large Graph Property Prediction via Graph Segment Training
- NeurIPS 2023Learning To Dive In Branch And Bound
- NeurIPS 2023Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets
- NeurIPS 2023Leveraging the two-timescale regime to demonstrate convergence of neural networks
- NeurIPS 2023Lie Point Symmetry and Physics-Informed Networks
- NeurIPS 2023Long Sequence Hopfield Memory
- NeurIPS 2023MAG-GNN: Reinforcement Learning Boosted Graph Neural Network
- NeurIPS 2023MathNAS: If Blocks Have a Role in Mathematical Architecture Design
- NeurIPS 2023Maximum Independent Set: Self-Training through Dynamic Programming
- NeurIPS 2023MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy
- NeurIPS 2023Modulated Neural ODEs
- NeurIPS 2023Module-wise Training of Neural Networks via the Minimizing Movement Scheme
- NeurIPS 2023Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum
- NeurIPS 2023Multiplication-Free Transformer Training via Piecewise Affine Operations
- NeurIPS 2023MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data
- NeurIPS 2023NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
- NeurIPS 2023NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks
- NeurIPS 2023Network Regression with Graph Laplacians
- NeurIPS 2023Neural (Tangent Kernel) Collapse
- NeurIPS 2023Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions
- NeurIPS 2023Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity
- NeurIPS 2023Neural Functional Transformers
- NeurIPS 2023Neural Graph Generation from Graph Statistics
- NeurIPS 2023Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem
- NeurIPS 2023Neural Lyapunov Control for Discrete-Time Systems
- NeurIPS 2023Neural Oscillators are Universal
- NeurIPS 2023Neural Processes with Stability
- NeurIPS 2023Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data
- NeurIPS 2023Neural Sculpting: Uncovering hierarchically modular task structure in neural networks through pruning and network analysis
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"}
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。