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Graph Neural Networks

1,141 papers

Papers per year

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Papers

Discourse-Level Event Temporal Ordering with Uncertainty-Guided Graph Completion IJCAI 2021
Recent Advances in Heterogeneous Relation Learning for Recommendation IJCAI 2021
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs IJCAI 2021
Graph-Based Label Propagation for Semi-Supervised Speaker Identification INTERSPEECH 2021
Determining the Number of Communities in Degree-corrected Stochastic Block Models JMLR 2021
On the Estimation of Network Complexity: Dimension of Graphons JMLR 2021
A Unified Framework for Spectral Clustering in Sparse Graphs JMLR 2021
A graph similarity for deep learning NIPS 2020
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning NIPS 2020
Towards Deeper Graph Neural Networks with Differentiable Group Normalization NIPS 2020
Dirichlet Graph Variational Autoencoder NIPS 2020
Graph Contrastive Learning with Augmentations NIPS 2020
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs NIPS 2020
Subgraph Neural Networks NIPS 2020
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks NIPS 2020
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks NIPS 2020
RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist NIPS 2020
Building powerful and equivariant graph neural networks with structural message-passing NIPS 2020
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks NIPS 2020
Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection Laplacian NIPS 2020
Random Walk Graph Neural Networks NIPS 2020
Path Integral Based Convolution and Pooling for Graph Neural Networks NIPS 2020
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection NIPS 2020
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models NIPS 2020
Hybrid Models for Learning to Branch NIPS 2020