A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models

Jiaxin Zhang 0009, Sirui Bi, Guannan Zhang. A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models. In Arindam Banerjee 0001, Kenji Fukumizu, editors, The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event. Volume 130 of Proceedings of Machine Learning Research, pages 3745-3753, PMLR, 2021. [doi]

@inproceedings{0009BZ21,
  title = {A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models},
  author = {Jiaxin Zhang 0009 and Sirui Bi and Guannan Zhang},
  year = {2021},
  url = {http://proceedings.mlr.press/v130/zhang21l.html},
  researchr = {https://researchr.org/publication/0009BZ21},
  cites = {0},
  citedby = {0},
  pages = {3745-3753},
  booktitle = {The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event},
  editor = {Arindam Banerjee 0001 and Kenji Fukumizu},
  volume = {130},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}