1. Blalock, D., Ortiz, J.J.G., Frankle, J., Guttag, J.: What is the State of Neural Network Pruning? (2020)
2. Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248–255. IEEE (2009)
3. Fock, E.: Global sensitivity analysis approach for input selection and system identification purposes-a new framework for feedforward neural networks. IEEE Trans. Neural Netw. Learn. Syst. 25, 1484–1495 (2014). https://doi.org/10.1109/TNNLS.2013.2294437
4. Han, S., Pool, J., Tran, J., Dally, W.J.: Learning both weights and connections for efficient neural networks. In: Proceedings of the 28th International Conference on Neural Information Processing Systems, vol. 1, pp. 1135–1143. NIPS’15, MIT Press, Cambridge, MA, USA (2015)
5. He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770–778 (2016)