LSTM是一种时间递归神经网络(RNN)[1],论文首次发表于1997年。由于独特的设计结构,LSTM适合于处理和预测时间序列中间隔和延迟非常长的重要事件。
  1. Understanding LSTM Networks -- colah's blog
  2. RNN and LSTM - handong1587 | TensorFlow RNN Tutorial
  3. 有哪些LSTM(Long Short Term Memory)和RNN(Recurrent)...
  4. 斯坦福CS231n课程作业# 3简介
  5. 揭开知识库问答KB-QA的面纱1·简介篇
  6. 高频交易实盘中,如何提高按对价(bid-ask)执行限价单(limit...
  7. 如何看待俄罗斯地底钻探到地狱入口之谜? - 知乎
  8. 《Improved Semantic Representations From Tree-Structured...
  9. 如何评价 Long Term Capital Management? - 知乎
  10. LSTM Networks应用于股票市场探究
  11. Deep State-based Model
  12. [Deep Learning] Long Short Term Memory - (LSTM) Networks
  13. Resources
  14. Sequence Models and Long-Short Term Memory Networks...
  15. 如何评价最近比较火的LSTM? - 知乎
  16. 《Bidirectional Recurrent Convolutional Neural Network for...
  17. Stages of Memory: Sensory, Short-Term, and Long-Term...
  18. 2.3 Long-Short Term Memory (LSTM) for Text Normalization
  19. 深度学习算法哪些适用于文本处理? - 知乎
  20. 有哪些LSTM(Long Short Term Memory)和RNN(Recurrent)...
展开全文
参考链接
微信扫码咨询专知VIP会员