J. Huggins, M. Kasprzak, T. Campbell, und T. Broderick. (2019)cite arxiv:1910.04102Comment: A python package for carrying out our validated variational inference workflow -- including doing black-box variational inference and computing the bounds we develop in this paper -- is available at https://github.com/jhuggins/viabel. The same repository also contains code for reproducing all of our experiments.
J. Hron, A. Matthews, und Z. Ghahramani. Proceedings of the 35th International Conference on Machine Learning, Volume 80 von Proceedings of Machine Learning Research, Seite 2019--2028. Stockholmsmässan, Stockholm Sweden, PMLR, (10--15 Jul 2018)
C. Chu, K. Minami, und K. Fukumizu. (2020)cite arxiv:2004.01822Comment: ICLR 2020, Workshop on Integration of Deep Neural Models and Differential Equations.
S. Chatzis. Proceedings of the 30th International Conference on Machine Learning, Volume 28 von Proceedings of Machine Learning Research, Seite 729--737. Atlanta, Georgia, USA, PMLR, (17--19 Jun 2013)