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 8 / 15 页

351. NeurIPS 2023Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer
352. NeurIPS 2023Differentiable and Stable Long-Range Tracking of Multiple Posterior Modes
353. NeurIPS 2023Differentiable sorting for censored time-to-event data.
354. NeurIPS 2023Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection
355. NeurIPS 2023Diffused Redundancy in Pre-trained Representations
356. NeurIPS 2023Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks
357. NeurIPS 2023Diffusion Probabilistic Models for Structured Node Classification
358. NeurIPS 2023Directional diffusion models for graph representation learning
359. NeurIPS 2023Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power
360. NeurIPS 2023Distributed Personalized Empirical Risk Minimization
361. NeurIPS 2023Distributionally Robust Skeleton Learning of Discrete Bayesian Networks
362. NeurIPS 2023DiViNeT: 3D Reconstruction from Disparate Views using Neural Template Regularization
363. NeurIPS 2023Does a sparse ReLU network training problem always admit an optimum ?
364. NeurIPS 2023Does Graph Distillation See Like Vision Dataset Counterpart?
365. NeurIPS 2023Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
366. NeurIPS 2023Don’t just prune by magnitude! Your mask topology is a secret weapon
367. NeurIPS 2023Double Gumbel Q-Learning
368. NeurIPS 2023DSR: Dynamical Surface Representation as Implicit Neural Networks for Protein
369. NeurIPS 2023Dynamic Sparsity Is Channel-Level Sparsity Learner
370. NeurIPS 2023Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes
371. NeurIPS 2023Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies
372. NeurIPS 2023Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
373. NeurIPS 2023DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
374. NeurIPS 2023Effective Bayesian Heteroscedastic Regression with Deep Neural Networks
375. NeurIPS 2023Efficient Beam Tree Recursion
376. NeurIPS 2023Efficient Learning of Linear Graph Neural Networks via Node Subsampling
377. NeurIPS 2023Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization
378. NeurIPS 2023Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks
379. NeurIPS 2023Efficiently incorporating quintuple interactions into geometric deep learning force fields
380. NeurIPS 2023EICIL: Joint Excitatory Inhibitory Cycle Iteration Learning for Deep Spiking Neural Networks
381. NeurIPS 2023Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity
382. NeurIPS 2023Empowering Convolutional Neural Nets with MetaSin Activation
383. NeurIPS 2023Encoding Human Behavior in Information Design through Deep Learning
384. NeurIPS 2023Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks
385. NeurIPS 2023Enhancing Sharpness-Aware Optimization Through Variance Suppression
386. NeurIPS 2023Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift
387. NeurIPS 2023Entropic Neural Optimal Transport via Diffusion Processes
388. NeurIPS 2023Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs
389. NeurIPS 2023Episodic Multi-Task Learning with Heterogeneous Neural Processes
390. NeurIPS 2023Epistemic Neural Networks
391. NeurIPS 2023Equivariant Neural Operator Learning with Graphon Convolution
392. NeurIPS 2023Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics
393. NeurIPS 2023ESSEN: Improving Evolution State Estimation for Temporal Networks using Von Neumann Entropy
394. NeurIPS 2023Euler-Lagrange Analysis of Generative Adversarial Networks
395. NeurIPS 2023Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
396. NeurIPS 2023Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis
397. NeurIPS 2023Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance
398. NeurIPS 2023Evolving Connectivity for Recurrent Spiking Neural Networks
399. NeurIPS 2023Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings
400. NeurIPS 2023Exact Verification of ReLU Neural Control Barrier Functions

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。