PaperHighlights

I read papers, and here are my highlights.

2018-11

• Learning Word Meta-Embeddings

• Frustratingly Easy Meta-Embedding – Computing Meta-Embeddings by Averaging Source Word Embeddings

2018-06

• Teaching Machines to Read and Comprehend

• Attention-over-Attention Neural Networks for Reading Comprehension

• Consensus Attention-based Neural Networks for Chinese Reading Comprehension

• Convolutional Neural Networks for Sentence Classification

• Deep contextualized word representations

• A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification

2018-05

• Attention Is All You Need

• Neural Machine Translation by Jointly Learning to Align and Translate

• U-Net: Convolutional Networks for Biomedical Image Segmentation

• Transforming Auto-encoders

• Text Understanding with the Attention Sum Reader Network

• Teaching Machines to Read and Comprehend

• An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

• Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

• Self-Attention with Relative Position Representations

• Deep Residual Learning for Image Recognition

• Memory Networks

• Hierarchical Attention Networks for Document Classification

• Graph Attention Networks

• Grammar as a Foreign Language

• Effective Approaches to Attention-based Neural Machine Translation

• Distance-based Self-Attention Network for Natural Language Inference

• Convolutional Sequence to Sequence Learning

• A Structured Self-attentive Sentence Embedding

• DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding

历史遗留笔记 (周记)

• 2018

  • 1

• 2017

  • 12

  • 11