A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments. Foster, A., Jankowiak, M., O'Meara, M., Teh, Y. W., & Rainforth, T. CoRR, 2019.
A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments [link]Paper  bibtex   
@article{DBLP:journals/corr/abs-1911-00294,
  author    = {Adam Foster and
               Martin Jankowiak and
               Matthew O'Meara and
               Yee Whye Teh and
               Tom Rainforth},
  title     = {A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal
               Experiments},
  journal   = {CoRR},
  volume    = {abs/1911.00294},
  year      = {2019},
  url       = {http://arxiv.org/abs/1911.00294},
  eprinttype = {arXiv},
  eprint    = {1911.00294},
  timestamp = {Mon, 11 Nov 2019 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-00294.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Downloads: 0