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Deep Learning
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Graph Neural Networks
4,495 papers
Papers per year
2006: 3
2009: 1
2010: 1
2011: 3
2012: 6
2013: 4
2014: 3
2015: 2
2016: 13
2017: 23
2018: 60
2019: 347
2020: 504
2021: 663
2022: 625
2023: 714
2024: 676
2025: 528
2026: 319
Papers
Leveraging Spatio-Temporal Dependency for Skeleton-Based Action Recognition
ICCV 2023
GlueStick: Robust Image Matching by Sticking Points and Lines Together
ICCV 2023
Visual Traffic Knowledge Graph Generation from Scene Images
ICCV 2023
Adaptive Spiral Layers for Efficient 3D Representation Learning on Meshes
ICCV 2023
Boosting Few-shot Action Recognition with Graph-guided Hybrid Matching
ICCV 2023
Vision HGNN: An Image is More than a Graph of Nodes
ICCV 2023
ReactioNet: Learning High-Order Facial Behavior from Universal Stimulus-Reaction by Dyadic Relation Reasoning
ICCV 2023
VQA-GNN: Reasoning with Multimodal Knowledge via Graph Neural Networks for Visual Question Answering
ICCV 2023
Spectral Augmentation for Self-Supervised Learning on Graphs
ICLR 2023
ClusterFuG: Clustering Fully connected Graphs by Multicut
ICML 2023
Half-Hop: A graph upsampling approach for slowing down message passing
ICML 2023
Personalized Subgraph Federated Learning
ICML 2023
Implicit Graph Neural Networks: A Monotone Operator Viewpoint
ICML 2023
TIDE: Time Derivative Diffusion for Deep Learning on Graphs
ICML 2023
Understanding Oversquashing in GNNs through the Lens of Effective Resistance
ICML 2023
Ske2Grid: Skeleton-to-Grid Representation Learning for Action Recognition
ICML 2023
Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network
ICML 2023
Fisher Information Embedding for Node and Graph Learning
ICML 2023
A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
ICML 2023
GREAD: Graph Neural Reaction-Diffusion Networks
ICML 2023
Taming graph kernels with random features
ICML 2023
Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks
ICML 2023
Distribution Free Prediction Sets for Node Classification
ICML 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
ICML 2023
Improving Graph Generation by Restricting Graph Bandwidth
ICML 2023
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