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Recurrent Neural Networks with over 30 LSTM papers by Jürgen Schmidhuber's group at Dalle Molle Institute for Artificial Intelligence Research
Gers, Felix (2001). “Long Short-Term Memory in Recurrent Neural Networks” (PDF). PhD thesis.
Gers, Felix A.; Schraudolph, Nicol N.; Schmidhuber, Jürgen (tháng 8 năm 2002). “Learning precise timing with LSTM recurrent networks” (PDF). Journal of Machine Learning Research 3: 115–143.
Abidogun, Olusola Adeniyi (2005). Data Mining, Fraud Detection and Mobile Telecommunications: Call Pattern Analysis with Unsupervised Neural Networks (PDF). Master's Thesis (Thesis) (University of the Western Cape). Bản gốc lưu trữ ngày 22 tháng 5 năm 2012. Đã bỏ qua tham số không rõ |url-status= (trợ giúp); Đã bỏ qua tham số không rõ |hdl= (trợ giúp)
- original with two chapters devoted to explaining recurrent neural networks, especially LSTM.
Monner, Derek D.; Reggia, James A. (2010). “A generalized LSTM-like training algorithm for second-order recurrent neural networks” (PDF). Neural Networks 25 (1): 70–83. PMC 3217173. PMID 21803542. doi:10.1016/j.neunet.2011.07.003. High-performing extension of LSTM that has been simplified to a single node type and can train arbitrary architectures
Dolphin, R. “LSTM Networks - A Detailed Explanation”. Article.
Herta, Christian. “How to implement LSTM in Python with Theano”. Tutorial.
Analyze the equation and build your own custom LSTM cell in Python. Tutorial

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