【論文解讀 EMNLP 2019 | MOGANED】ED with Multi-Order Graph Convolution and Aggregated Attention
論文題目：Event Detection with Multi-Order Graph Convolution and Aggregated Attention 論文來源：EMNLP 2019 論文鏈接：https://www.aclweb.org/anthology/D19-1582/ 代碼鏈接（非官方）：https://github.com/wzq016/MOGANED-Implementat
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相關文章
- 1. 【論文解讀 EMNLP 2018 | JMEE】Jointly Multiple EE via Attention-based Graph Information Aggregation
- 2. 【論文解讀 EMNLP 2019 | TLNN】Event Detection with Trigger-Aware Lattice Neural Network
- 3. 【論文解讀 EMNLP 2019】Joint Event and Temporal RE with Shared Representations and Structured Prediction
- 4. 【論文解讀 EMNLP 2019 | HMEAE】Hierarchical Modular Event Argument Extraction
- 5. 【論文解讀 arXiv 2020 | RA-GCN】Event Detection with Relation-Aware Graph Convolutional Networks
- 6. 《Heterogeneous Graph Attention Network》論文解讀
- 7. 【論文筆記】：Object detection with location-aware deformable convolution and backward attention filtering
- 8. 【論文解讀 AAAI 2018|GCN-ED】Graph Convolutional Networks with Argument-Aware Pooling for Event Detection
- 9. 【論文解讀 WWW 2019 | HAN】Heterogeneous Graph Attention Network
- 10. 《GRAPH ATTENTION NETWORKS》論文理解