1. Abadi, M., A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G.S. Corrado, A. Davis, J. Dean, M. Devin, S. Ghemawat, I. Goodfellow, A. Harp, G. Irving, M. Isard, Y. Jia, R. Jozefowicz, L. Kaiser, M. Kudlur, J. Levenberg, D. Mané, R. Monga, S. Moore, D. Murray, C. Olah, M. Schuster, J. Shlens, B. Steiner, I. Sutskever, K. Talwar, P. Tucker, V. Vanhoucke, V. Vasudevan, F. Viégas, O. Vinyals, P. Warden, M. Wattenberg, M. Wicke, Y. Yu, and X. Zheng (2015) TensorFlow: Large-scale machine learning on heterogeneous systems. tensorflow.org (accessed January 16, 2018).
2. IER Photochemical Smog Evaluation and Forecasting of Short-Term Ozone Pollution Levels with Artificial Neural Networks
3. Modelling interoccurrence times between ozone peaks in Mexico City in the presence of multiple change points
4. Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone