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 1,648 篇，第 19 / 33 页

901. NeurIPS 2024Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed
902. NeurIPS 2024TFGDA: Exploring Topology and Feature Alignment in Semi-supervised Graph Domain Adaptation through Robust Clustering
903. NeurIPS 2024The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks
904. NeurIPS 2024Towards Dynamic Message Passing on Graphs
905. NeurIPS 2024Towards Principled Graph Transformers
906. NeurIPS 2024Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network
907. NeurIPS 2024Transformers need glasses! Information over-squashing in language tasks
908. NeurIPS 2024UGC: Universal Graph Coarsening
909. NeurIPS 2024Uncovering the Redundancy in Graph Self-supervised Learning Models
910. NeurIPS 2024Unified Graph Augmentations for Generalized Contrastive Learning on Graphs
911. NeurIPS 2024Unifying Generation and Prediction on Graphs with Latent Graph Diffusion
912. NeurIPS 2024Unifying Homophily and Heterophily for Spectral Graph Neural Networks via Triple Filter Ensembles
913. NeurIPS 2024UniGAD: Unifying Multi-level Graph Anomaly Detection
914. NeurIPS 2024Unitary Convolutions for Learning on Graphs and Groups
915. NeurIPS 2024Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs
916. NeurIPS 2024Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning
917. NeurIPS 2024What do Graph Neural Networks learn? Insights from Tropical Geometry
918. NeurIPS 2024What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks
919. NeurIPS 2024What Matters in Graph Class Incremental Learning? An Information Preservation Perspective
920. NeurIPS 2024Why the Metric Backbone Preserves Community Structure
921. CVPR 2023Adaptive Graph Convolutional Subspace Clustering
922. CVPR 2023Adversarially Robust Neural Architecture Search for Graph Neural Networks
923. CVPR 2023An Actor-Centric Causality Graph for Asynchronous Temporal Inference in Group Activity
924. CVPR 2023Deep Graph Reprogramming
925. CVPR 2023Deep Graph-Based Spatial Consistency for Robust Non-Rigid Point Cloud Registration
926. CVPR 2023Deep Learning of Partial Graph Matching via Differentiable Top-K
927. CVPR 2023Graph Representation for Order-Aware Visual Transformation
928. CVPR 2023High Fidelity 3D Hand Shape Reconstruction via Scalable Graph Frequency Decomposition
929. CVPR 2023Highly Confident Local Structure Based Consensus Graph Learning for Incomplete Multi-View Clustering
930. CVPR 2023Histopathology Whole Slide Image Analysis With Heterogeneous Graph Representation Learning
931. CVPR 2023Improving Graph Representation for Point Cloud Segmentation via Attentive Filtering
932. CVPR 2023Incremental 3D Semantic Scene Graph Prediction From RGB Sequences
933. CVPR 2023Mind the Label Shift of Augmentation-Based Graph OOD Generalization
934. CVPR 2023Multi-Granularity Archaeological Dating of Chinese Bronze Dings Based on a Knowledge-Guided Relation Graph
935. CVPR 2023Robust 3D Shape Classification via Non-Local Graph Attention Network
936. CVPR 2023Sample-Level Multi-View Graph Clustering
937. CVPR 2023TopDiG: Class-Agnostic Topological Directional Graph Extraction From Remote Sensing Images
938. CVPR 2023Transductive Few-Shot Learning With Prototype-Based Label Propagation by Iterative Graph Refinement
939. CVPR 2023TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning With Structure-Trajectory Prompted Reconstruction for Person Re-Identification
940. CVPR 2023Tree Instance Segmentation With Temporal Contour Graph
941. CVPR 2023Turning Strengths Into Weaknesses: A Certified Robustness Inspired Attack Framework Against Graph Neural Networks
942. CVPR 2023VectorFloorSeg: Two-Stream Graph Attention Network for Vectorized Roughcast Floorplan Segmentation
943. CVPR 2023VL-SAT: Visual-Linguistic Semantics Assisted Training for 3D Semantic Scene Graph Prediction in Point Cloud
944. ICLR 2023$\mathscr{N}$-WL: A New Hierarchy of Expressivity for Graph Neural Networks
945. ICLR 2023$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks
946. ICLR 2023A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
947. ICLR 2023A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps
948. ICLR 2023A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
949. ICLR 2023Agent-based Graph Neural Networks
950. ICLR 2023Anti-Symmetric DGN: a stable architecture for Deep Graph 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。