ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs（閱讀理解）
首先這張圖片是本文的基礎模型，後續的工作以此展開。BCNN是一個沒有添加Attention的模型 輸入層 輸入句子進行padding後轉化成詞向量 卷積層 一個窗口最後只生成一個卷積值，然後再句子長度上進行滑動，得到一個長度爲sent_len+ws-1的向量（wide conv） pooling層 論文中提到了兩種pooling層，一種是最後一個pooling層–all-ap，還有一種是中間卷積
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相關文章
- 1. 《ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs》
- 2. ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs論文解讀
- 3. Convolutional Neural Networks for Sentence Classification（閱讀理解）
- 4. Convolutional Neural Network For Sentence Classification
- 5. Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks（閱讀理解）
- 6. 論文閱讀：《Convolutional Neural Networks for Sentence Classification》
- 7. Convolutional Neural Networks for Sentence Classification 閱讀筆記
- 8. Multiway Attention Networks for Modeling Sentence Pairs
- 9. Deep Neural Network for Learning to Rank Query-Text Pairs閱讀筆記
- 10. Convolutional Neural Network Architectures for Matching Natural Language Sentences（閱讀理解）