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 728 篇，第 10 / 15 页

451. NeurIPS 2023Graph of Circuits with GNN for Exploring the Optimal Design Space
452. NeurIPS 2023Graph-Structured Gaussian Processes for Transferable Graph Learning
453. NeurIPS 2023GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search
454. NeurIPS 2023GSLB: The Graph Structure Learning Benchmark
455. NeurIPS 2023GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
456. NeurIPS 2023Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition
457. NeurIPS 2023Hierarchical Randomized Smoothing
458. NeurIPS 2023High dimensional, tabular deep learning with an auxiliary knowledge graph
459. NeurIPS 2023HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation
460. NeurIPS 2023How Does Adaptive Optimization Impact Local Neural Network Geometry?
461. NeurIPS 2023HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork
462. NeurIPS 2023Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach
463. NeurIPS 2023Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
464. NeurIPS 2023Hypervolume Maximization: A Geometric View of Pareto Set Learning
465. NeurIPS 2023Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network
466. NeurIPS 2023Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data
467. NeurIPS 2023Implicit Manifold Gaussian Process Regression
468. NeurIPS 2023Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics
469. NeurIPS 2023Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization
470. NeurIPS 2023Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings
471. NeurIPS 2023Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
472. NeurIPS 2023Improving neural network representations using human similarity judgments
473. NeurIPS 2023Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training
474. NeurIPS 2023Individualized Dosing Dynamics via Neural Eigen Decomposition
475. NeurIPS 2023Information Geometry of the Retinal Representation Manifold
476. NeurIPS 2023Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks
477. NeurIPS 2023Inner Product-based Neural Network Similarity
478. NeurIPS 2023Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks
479. NeurIPS 2023Interpretable Graph Networks Formulate Universal Algebra Conjectures
480. NeurIPS 2023Interpretable Prototype-based Graph Information Bottleneck
481. NeurIPS 2023Investigating how ReLU-networks encode symmetries
482. NeurIPS 2023Is Distance Matrix Enough for Geometric Deep Learning?
483. NeurIPS 2023Joint Training of Deep Ensembles Fails Due to Learner Collusion
484. NeurIPS 2023KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training
485. NeurIPS 2023Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
486. NeurIPS 2023Labeling Neural Representations with Inverse Recognition
487. NeurIPS 2023LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
488. NeurIPS 2023Language Semantic Graph Guided Data-Efficient Learning
489. NeurIPS 2023Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
490. NeurIPS 2023Large sample spectral analysis of graph-based multi-manifold clustering
491. NeurIPS 2023LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer
492. NeurIPS 2023Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
493. NeurIPS 2023Latent Graph Inference with Limited Supervision
494. NeurIPS 2023Layer-Neighbor Sampling --- Defusing Neighborhood Explosion in GNNs
495. NeurIPS 2023LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
496. NeurIPS 2023Learning and processing the ordinal information of temporal sequences in recurrent neural circuits
497. NeurIPS 2023Learning DAGs from Data with Few Root Causes
498. NeurIPS 2023Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization
499. NeurIPS 2023Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
500. NeurIPS 2023Learning Functional Transduction

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。