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GPNet: Simplifying Graph Neural Networks via Multi-channel Geometric Polynomials
Graph Neural Networks (GNNs) are a promising deep learning approach for circumventing many real-world problems on graph-structured data.
PatentNet: A Large-Scale Incomplete Multiview, Multimodal, Multilabel Industrial Goods Image Database
In deep learning area, large-scale image datasets bring a breakthrough in the success of object recognition and retrieval.
Hybrid Low-order and Higher-order Graph Convolutional Networks
With higher-order neighborhood information of graph network, the accuracy of graph representation learning classification can be significantly improved.
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