【KDD 2019】Is a Single Vector Enough Exploring Node Polysemy for Network Embedding
摘要 Networks have been widely used as the data structure for abstracting real-world systems as well as organizing the relations among entities. Network embedding models are powerful tools in mapping no
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相關文章
- 1. 【KDD 2019】Heterogeneous Graph Neural Network
- 2. EmbeddingVis: A Visual Analytics Approach to Comparative Network Embedding Inspection
- 3. 【KDD 2019】A Representation Learning Framework for Property Graphs
- 4. A Survey of Network Embedding
- 5. 【論文解讀 KDD 2019 | GATNE 】Representation Learning for Attributed Multiplex Heterogeneous Network
- 6. 【論文解讀 KDD 2019 | MEIRec】Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation
- 7. Exploring the Network
- 8. A Cascaded Convolutional Neural Network for Single Image Dehazing
- 9. SRMD:Learning a Single Convolutional Super-Resolution Network for Multiple Degradations
- 10. network embedding