Variational Bayesian Optimal Experimental Design. Foster, A., Jankowiak, M., Bingham, E., Horsfall, P., Teh, Y. W., Rainforth, T., & Goodman, N. D. In Wallach, H. M., Larochelle, H., Beygelzimer, A., d'Alché-Buc , F., Fox, E. B., & Garnett, R., editors, Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, pages 14036–14047, 2019. Paper bibtex @inproceedings{DBLP:conf/nips/FosterJBHTRG19,
author = {Adam Foster and
Martin Jankowiak and
Eli Bingham and
Paul Horsfall and
Yee Whye Teh and
Tom Rainforth and
Noah D. Goodman},
editor = {Hanna M. Wallach and
Hugo Larochelle and
Alina Beygelzimer and
Florence d'Alch{\'{e}}{-}Buc and
Emily B. Fox and
Roman Garnett},
title = {Variational Bayesian Optimal Experimental Design},
booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference
on Neural Information Processing Systems 2019, NeurIPS 2019, December
8-14, 2019, Vancouver, BC, Canada},
pages = {14036--14047},
year = {2019},
url = {https://proceedings.neurips.cc/paper/2019/hash/d55cbf210f175f4a37916eafe6c04f0d-Abstract.html},
timestamp = {Thu, 21 Jan 2021 00:00:00 +0100},
biburl = {https://dblp.org/rec/conf/nips/FosterJBHTRG19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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