Below a non-complete list of references and readings related to TOC4Deep. Let us know if your work has not been acknowledged!
[1] Strubell, E., Ganesh, A., McCallum, A., Energy and Policy Considerations for Deep Learning in NLP. Preprint (2019). ArXiv:1906.02243.
[2] Henderson P., Hu, J., Romoff J., Brunskill, E., Jurafsky, D., Pineau, J., Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. Preprint (2020). ArXiv:2002.05651.
[3] van Wynsberghe A., Sustainable AI: AI for sustainability and the sustainability of AI. AI and Ethics (2021) Vol. 1, pp. 213-218.
[4] Vinuesa, R., Azizpour, H., Leite, I. et al, The role of artificial intelligence in achieving the Sustainable Development Goals. Nat Commun Vol. 11, n. 233 (2020).
[5] Higham, C. F. and Higham, D. J., Deep Learning: An Introduction for Applied Mathematicians. SIAM Review Vol. 61, n. 4, pp. 860-891 (2019).
[6] Benning, M., Celledoni, E., Ehrhardt, M. J., Owren, B. and Schönlieb, C.-B., Deep Learning as Optimal Control Problems: Models and Numerical Methods. Preprint (2019). ArXiv: 1904.05657.
[7] Haber, E. and Ruthotto, L., Stable architectures for deep neural networks. Inverse Problems (2018) Vol. 34, n. 1.
[8] LeCun, Y., Bengio, Y. and Hinton, G. Deep learning. Nature (2015) Vol. 521, pp. 436-444.
[9] Ruthotto, L., Haber, E. Deep Neural Networks Motivated by Partial Differential Equations. J Math Imaging Vis (2020) Vol. 62, p. 352-364.
[10] Silver, D. and Hassabis, D.. https://deepmind.com/blog/article/alphago-zero-starting-scratch, 2017.
[11] Leveque, S. and Pearson, J. W., Fast Iterative Solver for the Optimal Control of Time-Dependent PDEs with Crank-Nicolson Discretization in Time. Preprint (2020). ArXiv: 2007.08410
[12] Pearson, J. W., Porcelli, M. and Stoll, S., Interior Point Methods and Preconditioning for PDE-Constrained Optimization Problems Involving Sparsity Terms, Numerical Linear Algebra with Applications (2020), Vol. 27, n.2.
[13] Stoll, M. and Wathen, A., Preconditioning for partial differential equation constrained optimization with control constraints. Numerical Linear Algebra with Applications (2012), Vol. 19, pp. 53-71.
[14] Hinze, M., Pinnau, R., Ulbrich, M., and Ulbrich, S.. Optimization with PDE constraints. Springer Science & Business Media, (2008) Vol. 23.
[15] Benzi, M., Golub, G., and Liesen, J. Numerical solution of saddle point problems. Acta Numerica (2005), Vol. 14, pp. 1-137.
[16] Goodfellow, I., Bengio, Y. and Courville, A.. Deep Learning, MIT Press (2016).
[17] Oseledets, I. V.. Tensor-Train Decomposition, SIAM J. Sci. Comput. (2011), Vol. 33, n. 5, pp. 2295-2317.
[18] Yang, Y., Krompass, D., and Tresp, V.. Proceedings of the 34th International Conference on Machine Learning, (2017), pp. 3891-3900.
[19] Dolgov, S. V.. TT-GMRES: solution to a linear system in the structured tensor format Russian Journal of Numerical Analysis and Mathematical Modelling (2013), Vol. 28, no. 2, pp. 149-172.
[20] Benzi, M.. Preconditioning Techniques for Large Linear Systems: A Survey, Journal of Computational Physics (2002), Vol. 182, n. 2, pp 418-477.