Long Short-Term Memory (LSTM)

最新推荐文章于 2023-07-08 11:57:31 发布

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最新推荐文章于 2023-07-08 11:57:31 发布

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原文链接：http://www.cnblogs.com/AcceptedLin/p/9778953.html

本文深入探讨了长短期记忆网络（LSTM），一种特殊类型的循环神经网络（RNN），旨在解决长期依赖问题。从背景到定义，再到LSTM网络的具体结构，文章详细介绍了LSTM的工作原理及其与传统RNN的区别。此外，还提到了LSTM的扩展形式——门控循环单元（GRU），并通过实例展示了LSTM的应用。参考了多篇权威文献，为读者提供了全面的LSTM理解视角。

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Long Short-Term Memory (LSTM)

Outline

Background

LSTM Network

Extended LSTM

LSTM vs. RNN

Examples

References

Background

Definition

LSTM Network

For detailed derivation: http://cs224d.stanford.edu/

Extended LSTM---GRU

LSTM vs. RNN

References

1.A. Graves. Supervised Sequence Labelling with Recurrent Neural Networks. Textbook, Studies in Computational Intelligence, Springer, 2012

2.Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8), 1735-1780

3.Gers, F. A., Schmidhuber, J., & Cummins, F. (2000). Learning to forget: Continual prediction with LSTM. Neural computation, 12(10), 2451-2471

4.Graves, Alex. Supervised sequence labelling with recurrent neural networks. Vol. 385. Springer, 2012

5.Bastien, Frédéric, Lamblin, Pascal, Pascanu, Razvan, Bergstra, James, Goodfellow, Ian, Bergeron, Arnaud, Bouchard, Nicolas, and Bengio, Yoshua. Theano: new features and speed improvements. NIPS Workshop on Deep Learning and Unsupervised Feature Learning, 2012

转载于:https://www.cnblogs.com/AcceptedLin/p/9778953.html