1. Abdel-Hamid, O., Deng, L., & Yu, D. (2013). Exploring convolutional neural network structures and optimization techniques for speech recognition. In Interspeech (Vol. 2013, pp. 3366–3370).
https://pdfs.semanticscholar.org/655a/e6f82c24e3e01b2b27c56512b06ba36d49c1.pdf
. Accessed 15 Feb 2018.
2. Bengio, Y. (2009). Learning deep architectures for AI. Foundations and Trends® in Machine Learning,2(1), 1–127.
https://doi.org/10.1561/2200000006
.
3. García, V., Sánchez, J. S., Rodríguez-Picón, L. A., Méndez-González, L. C., & de Jesús Ochoa-Domínguez, H. (2018). Using regression models for predicting the product quality in a tubing extrusion process. Journal of Intelligent Manufacturing.
https://doi.org/10.1007/s10845-018-1418-7
.
4. Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial nets. In Proceedings of neural information processing systems (pp. 2672–2680).
5. Graves, A. (2013). Generating sequences with recurrent neural networks. arXiv preprint
arXiv:1308.0850
.