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

每年论文数

各会议论文数

按年份和会议统计

深度学习 · graph neural networks论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
20234896814823728
2024160517610297
2025915014115297
20261023216824326

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

全部深度学习 · graph neural networks论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 1,648 篇，第 28 / 33 页

  1. NeurIPS 2023Generalization bounds for neural ordinary differential equations and deep residual networks
  2. NeurIPS 2023Generating Behaviorally Diverse Policies with Latent Diffusion Models
  3. NeurIPS 2023Geometry-Informed Neural Operator for Large-Scale 3D PDEs
  4. NeurIPS 2023GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising
  5. NeurIPS 2023GEQ: Gaussian Kernel Inspired Equilibrium Models
  6. NeurIPS 2023GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning
  7. NeurIPS 2023GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection
  8. NeurIPS 2023Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization
  9. NeurIPS 2023Globally injective and bijective neural operators
  10. NeurIPS 2023GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels
  11. NeurIPS 2023Goal-conditioned Offline Planning from Curious Exploration
  12. NeurIPS 2023Going beyond persistent homology using persistent homology
  13. NeurIPS 2023GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks
  14. NeurIPS 2023Gradient-Based Feature Learning under Structured Data
  15. NeurIPS 2023Graph Clustering with Graph Neural Networks
  16. NeurIPS 2023Graph Contrastive Learning with Stable and Scalable Spectral Encoding
  17. NeurIPS 2023Graph Convolutional Kernel Machine versus Graph Convolutional Networks
  18. NeurIPS 2023Graph Denoising Diffusion for Inverse Protein Folding
  19. NeurIPS 2023Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
  20. NeurIPS 2023Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis
  21. NeurIPS 2023Graph of Circuits with GNN for Exploring the Optimal Design Space
  22. NeurIPS 2023Graph-Structured Gaussian Processes for Transferable Graph Learning
  23. NeurIPS 2023GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search
  24. NeurIPS 2023GSLB: The Graph Structure Learning Benchmark
  25. NeurIPS 2023GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
  26. NeurIPS 2023Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition
  27. NeurIPS 2023Hierarchical Randomized Smoothing
  28. NeurIPS 2023High dimensional, tabular deep learning with an auxiliary knowledge graph
  29. NeurIPS 2023HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation
  30. NeurIPS 2023How Does Adaptive Optimization Impact Local Neural Network Geometry?
  31. NeurIPS 2023HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork
  32. NeurIPS 2023Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach
  33. NeurIPS 2023Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
  34. NeurIPS 2023Hypervolume Maximization: A Geometric View of Pareto Set Learning
  35. NeurIPS 2023Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network
  36. NeurIPS 2023Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data
  37. NeurIPS 2023Implicit Manifold Gaussian Process Regression
  38. NeurIPS 2023Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics
  39. NeurIPS 2023Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization
  40. NeurIPS 2023Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings
  41. NeurIPS 2023Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
  42. NeurIPS 2023Improving neural network representations using human similarity judgments
  43. NeurIPS 2023Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training
  44. NeurIPS 2023Individualized Dosing Dynamics via Neural Eigen Decomposition
  45. NeurIPS 2023Information Geometry of the Retinal Representation Manifold
  46. NeurIPS 2023Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks
  47. NeurIPS 2023Inner Product-based Neural Network Similarity
  48. NeurIPS 2023Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks
  49. NeurIPS 2023Interpretable Graph Networks Formulate Universal Algebra Conjectures
  50. NeurIPS 2023Interpretable Prototype-based Graph Information Bottleneck

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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"}

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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。

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