• Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8), 1735-1780.
• Gers, F. A., Schmidhuber, J., & Cummins, F. (2000). Learning to forget: Continual prediction with LSTM. Neural computation, 12(10), 2451-2471.
• Graves, Alex. Supervised sequence labeling with recurrent neural networks. Vol. 385. Springer, 2012.

• Y. Bengio, P. Simard, and P. Frasconi. Learning long-term dependencies with gradient descent is difficult. IEE TRANSACTIONS ON NEURAL NETWORKS, 5, 1994.
• F. Chollet. Keras github.
• J. Chung, C. Gulcehre, K. Cho, and Y. Bengio. Empirical evaluation of gated recurrent neural networks on sequence modeling, 2014.
• S. Hochreiter and J. Schmidhuber. Long short-term memory. Neural Computation, 9:1735–1780, 1997.
• Q. V. Le, N. Jaitly, and H. G. E. A simple way to initialize recurrent networks of rectified linear units. 2015.
• Y. Lu and F. Salem. Simplified gating in long short-term memory (lstm) recurrent neural networks. arXiv:1701.03441, 2017.
• F. M. Salem. A basic recurrent neural network model. arXiv preprint arXiv:1612.09022, 2016.
• F. M. Salem. Reduced parameterization of gated recurrent neural networks. MSU Memorandum, 7.11.2016.