帮我查询关于LSTM的参考文献
时间: 2023-03-12 18:07:17 浏览: 93
我可以为您推荐一些关于LSTM的参考文献,包括:1. Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8), 1735-1780. 2. Graves, A. (2013). Generating sequences with recurrent neural networks. arXiv preprint arXiv:1308.0850. 3. Gers, F. A., Schraudolph, N. N., & Schmidhuber, J. (2000). Learning to forget: Continual prediction with LSTM. Neural computation, 12(10), 2451-2471. 4. Olah, C., Carter, S., Schubert, L., & Ye, Q. (2015). Understanding LSTM networks. 5. Greff, K., Srivastava, R. K., Koutník, J., Steunebrink, B. R., & Schmidhuber, J. (2016). LSTM: A search space odyssey. IEEE transactions on neural networks and learning systems, 28(10), 2222-2232.
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cnn-lstm参考文献
CNN-LSTM是一种深度学习模型,结合了卷积神经网络(Convolutional Neural Network,CNN)和长短期记忆网络(Long Short-Term Memory,LSTM)的特点,常用于处理序列数据。以下是一些关于CNN-LSTM的参考文献:
1. Shi, X., Chen, Z., Wang, H., Yeung, D. Y., Wong, W. K., & Woo, W. C. (2015). Convolutional LSTM network: A machine learning approach for precipitation nowcasting. In Advances in neural information processing systems (pp. 802-810). 这篇论文介绍了CNN-LSTM网络在天气预测中的应用。
2. Karim, F., Majumdar, S., Darabi, H., & Chen, S. (2018). LSTM fully convolutional networks for time series classification. IEEE Access, 6, 1662-1669. 这篇论文探讨了将LSTM和卷积神经网络结合的方法,用于时间序列分类任务。
3. Bai, S., Kolter, J. Z., & Koltun, V. (2018). An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271. 这篇论文对CNN-LSTM等模型进行了实证研究,比较了它们在序列建模任务上的表现。
4. Wang, L., & Wang, J. (2018). Modeling attention in LSTM for multimodal sentiment analysis. Neurocomputing, 282, 105-113. 这篇论文利用CNN-LSTM模型进行多模态情感分析,并引入了注意力机制来提升模型性能。
tpthon lstm 参考文献
以下是关于 Python LSTM 的一些参考文献:
1. [Keras LSTM文档](https://keras.io/layers/recurrent/)
2. [TensorFlow LSTM文档](https://www.tensorflow.org/api_docs/python/tf/keras/layers/LSTM)
3. [Python深度学习:基于Keras的实践](https://book.douban.com/subject/30293801/)
4. [Python深度学习](https://book.douban.com/subject/27087503/)
5. [Python深度学习编程](https://book.douban.com/subject/30412965/)
6. [LSTM Networks for Sentiment Analysis](https://towardsdatascience.com/lstm-networks-for-sentiment-analysis-cefa5e8b06bc)