How powerful are graph neural networks?
How powerful are graph neural networks? ICLR 2019 背景 1.圖神經網絡 圖神經網絡及其應用 2.Weisfeiler-Lehman test 同構：如果圖G1和G2的頂點和邊的數目相同，並且邊的連通性相同，則這兩個圖可以說是同構的，如下圖所示。也可以認爲G2的頂點是從G1的頂點映射而來的。這是一個具有挑戰性的問題：目前還沒有已知的多項式時間算法。圖
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相關文章
- 1. HOW POWERFUL ARE GRAPH NEURAL NETWORKS?
- 2. How Powerful are Graph Neural Networks？ GIN 圖同構網絡 ICLR 2019 論文詳解
- 3. How to Implement Neural Networks with TensorFlow
- 4. CS224W-08-Graph Neural Networks
- 5. How convolution neural networks work
- 6. How transferable are features in deep neural networks?
- 7. How are neural networks related to Fourier transforms
- 8. Applications of Graph Neural Networks
- 9. Graph Neural Networks for Social Recommendation
- 10. GMNN: Graph Markov Neural Networks