ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs（阅读理解）
首先这张图片是本文的基础模型，后续的工作以此展开。BCNN是一个没有添加Attention的模型 输入层 输入句子进行padding后转化成词向量 卷积层 一个窗口最后只生成一个卷积值，然后再句子长度上进行滑动，得到一个长度为sent_len+ws-1的向量（wide conv） pooling层 论文中提到了两种pooling层，一种是最后一个pooling层–all-ap，还有一种是中间卷积
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相关文章
- 1. 《ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs》
- 2. ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs论文解读
- 3. Convolutional Neural Networks for Sentence Classification（阅读理解）
- 4. Convolutional Neural Network For Sentence Classification
- 5. Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks（阅读理解）
- 6. 论文阅读：《Convolutional Neural Networks for Sentence Classification》
- 7. Convolutional Neural Networks for Sentence Classification 阅读笔记
- 8. Multiway Attention Networks for Modeling Sentence Pairs
- 9. Deep Neural Network for Learning to Rank Query-Text Pairs阅读笔记
- 10. Convolutional Neural Network Architectures for Matching Natural Language Sentences（阅读理解）