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| "title": "Hyperbolic Graph Convolutional Neural Networks" |
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| "title": "Adversarial Attacks on Graph Neural Networks via Meta Learning" |
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| "title": "Explainability in Graph Neural Networks: A Taxonomic Survey" |
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| "title": "Graph Convolutional Encoders for Syntax-aware Neural Machine Translation" |
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| "title": "Graph Convolutional Networks for Temporal Action Localization" |
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| "title": "Graph Self-Supervised Learning: A Survey" |
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| "title": "Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search" |
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| "title": "KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning" |
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| "title": "Coherent Comments Generation for Chinese Articles with a Graph-to-Sequence Model" |
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| "1902.00175": { |
| "arxivId": "1902.00175", |
| "title": "Dating Documents using Graph Convolution Networks" |
| }, |
| "1808.06354": { |
| "arxivId": "1808.06354", |
| "title": "Signed Graph Convolutional Network" |
| }, |
| "1905.13728": { |
| "arxivId": "1905.13728", |
| "title": "Pre-Training Graph Neural Networks for Generic Structural Feature Extraction" |
| }, |
| "1903.04154": { |
| "arxivId": "1903.04154", |
| "title": "Fisher-Bures Adversary Graph Convolutional Networks" |
| }, |
| "1805.09980": { |
| "arxivId": "1805.09980", |
| "title": "Deep Graph Translation" |
| }, |
| "1912.12408": { |
| "arxivId": "1912.12408", |
| "title": "RoadTagger: Robust Road Attribute Inference with Graph Neural Networks" |
| }, |
| "1903.01888": { |
| "arxivId": "1903.01888", |
| "title": "Gated Graph Convolutional Recurrent Neural Networks" |
| }, |
| "2010.12609": { |
| "arxivId": "2010.12609", |
| "title": "Iterative Graph Self-Distillation" |
| }, |
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| "arxivId": "1910.13445", |
| "title": "G2SAT: Learning to Generate SAT Formulas" |
| }, |
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| "arxivId": "1905.08636", |
| "title": "Joint embedding of structure and features via graph convolutional networks" |
| }, |
| "1903.02174": { |
| "arxivId": "1903.02174", |
| "title": "Graph Neural Networks for User Identity Linkage" |
| }, |
| "1809.09925": { |
| "arxivId": "1809.09925", |
| "title": "Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning" |
| }, |
| "2009.01674": { |
| "arxivId": "2009.01674", |
| "title": "CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning" |
| }, |
| "1811.06930": { |
| "arxivId": "1811.06930", |
| "title": "Pre-training Graph Neural Networks with Kernels" |
| }, |
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| "arxivId": "2005.08008", |
| "title": "Graph Partitioning and Graph Neural Network based Hierarchical Graph Matching for Graph Similarity Computation" |
| }, |
| "1905.06515": { |
| "arxivId": "1905.06515", |
| "title": "ncRNA Classification with Graph Convolutional Networks" |
| }, |
| "1902.08399": { |
| "arxivId": "1902.08399", |
| "title": "Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations" |
| }, |
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| "arxivId": "2001.07108", |
| "title": "Spectral Pyramid Graph Attention Network for Hyperspectral Image Classification" |
| }, |
| "1903.07518": { |
| "arxivId": "1903.07518", |
| "title": "Extrapolating paths with graph neural networks" |
| }, |
| "2001.00293": { |
| "arxivId": "2001.00293", |
| "title": "Deep Learning for Learning Graph Representations" |
| }, |
| "1810.08403": { |
| "arxivId": "1810.08403", |
| "title": "Towards Efficient Large-Scale Graph Neural Network Computing" |
| }, |
| "1809.07695": { |
| "arxivId": "1809.07695", |
| "title": "Multitask Learning on Graph Neural Networks - Learning Multiple Graph Centrality Measures with a Unified Network" |
| }, |
| "1807.02653": { |
| "arxivId": "1807.02653", |
| "title": "When Work Matters: Transforming Classical Network Structures to Graph CNN" |
| }, |
| "1709.02314": { |
| "arxivId": "1709.02314", |
| "title": "Representation Learning for Visual-Relational Knowledge Graphs" |
| }, |
| "1707.04677": { |
| "arxivId": "1707.04677", |
| "title": "Knowledge-guided recurrent neural network learning for task-oriented action prediction" |
| }, |
| "1803.10071": { |
| "arxivId": "1803.10071", |
| "title": "Tensor graph convolutional neural network" |
| }, |
| "2001.01290": { |
| "arxivId": "2001.01290", |
| "title": "General Partial Label Learning via Dual Bipartite Graph Autoencoder" |
| }, |
| "1911.05469": { |
| "arxivId": "1911.05469", |
| "title": "Multi-MotifGAN (MMGAN): Motif-Targeted Graph Generation And Prediction" |
| }, |
| "1905.03046": { |
| "arxivId": "1905.03046", |
| "title": "PiNet: A Permutation Invariant Graph Neural Network for Graph Classification" |
| }, |
| "1901.02078": { |
| "arxivId": "1901.02078", |
| "title": "All Graphs Lead to Rome: Learning Geometric and Cycle-Consistent Representations with Graph Convolutional Networks" |
| }, |
| "1811.00497": { |
| "arxivId": "1811.00497", |
| "title": "Modeling Attention Flow on Graphs" |
| }, |
| "1811.00538": { |
| "arxivId": "1811.00538", |
| "title": "Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering" |
| }, |
| "1805.07683": { |
| "arxivId": "1805.07683", |
| "title": "Learning Graph-Level Representations with Recurrent Neural Networks" |
| }, |
| "1906.01852": { |
| "arxivId": "1906.01852", |
| "title": "Variational Spectral Graph Convolutional Networks" |
| }, |
| "1902.06667": { |
| "arxivId": "1902.06667", |
| "title": "Semi-supervised Node Classification via Hierarchical Graph Convolutional Networks" |
| }, |
| "1905.06707": { |
| "arxivId": "1905.06707", |
| "title": "Inferring Javascript types using Graph Neural Networks" |
| }, |
| "1905.06259": { |
| "arxivId": "1905.06259", |
| "title": "Function Space Pooling For Graph Convolutional Networks" |
| }, |
| "1808.07769": { |
| "arxivId": "1808.07769", |
| "title": "Topology and Prediction Focused Research on Graph Convolutional Neural Networks" |
| } |
| } |
