Graph Neural Networks
5,491 papers
Papers per year
3
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1
3
7
4
3
2
13
23
66
348
550
686
703
817
962
904
395
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Papers
Joint Representation Learning of Legislator and Legislation for Roll Call Prediction
IJCAI 2020
Knowledge and Cross-Pair Pattern Guided Semantic Matching for Question Answering
AAAI 2020
Knowledge Association with Hyperbolic Knowledge Graph Embeddings
EMNLP 2020
Knowledge Graph Alignment Network with Gated Multi-Hop Neighborhood Aggregation
AAAI 2020
Knowledge Graph Alignment with Entity-Pair Embedding
EMNLP 2020
Knowledge Graph and Deep Neural Network for Extractive Text Summarization by Utilizing Triples
COLING 2020
Knowledge Graph Transfer Network for Few-Shot Recognition
AAAI 2020
Kriging Convolutional Networks
AAAI 2020
L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks
CVPR 2020
LambdaNet: Probabilistic Type Inference using Graph Neural Networks
ICLR 2020
Learning 3D Semantic Scene Graphs From 3D Indoor Reconstructions
CVPR 2020
Learning Algebraic Multigrid Using Graph Neural Networks
ICML 2020
Learning a Neural Solver for Multiple Object Tracking
CVPR 2020
Learning-Based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching
AAAI 2020
Learning Combinatorial Solver for Graph Matching
CVPR 2020
Learning Compositional Koopman Operators for Model-Based Control
ICLR 2020
Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations
NeurIPS 2020
Learning Cross-Modal Context Graph for Visual Grounding
AAAI 2020
Learning deep graph matching with channel-independent embedding and Hungarian attention
ICLR 2020
Learning Dynamic Context Graph Embedding
ACML 2020
Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification
AISTATS 2020
Learning Dynamic Relationships for 3D Human Motion Prediction
CVPR 2020
LEARNING EXECUTION THROUGH NEURAL CODE FUSION
ICLR 2020
Learning for Graph Matching and Related Combinatorial Optimization Problems
IJCAI 2020
Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks
AAAI 2020