A. Matthews, M. Rowland, J. Hron, R. Turner, and Z. Ghahramani. (2018)cite arxiv:1804.11271Comment: This work substantially extends the work of Matthews et al. (2018) published at the International Conference on Learning Representations (ICLR) 2018.
G. Yang. (2019)cite arxiv:1902.04760Comment: tldr: A theoretical tool for understanding the behavior of large width randomly initialized neural networks for almost all deep learning architectures.