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Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks

2019

Conference Paper

ei


Author(s): von Kügelgen, J. and Rubenstein, P. K. and Schölkopf, B. and Weller, A.
Book Title: NeurIPS 2019 Workshop Do the right thing: machine learning and causal inference for improved decision making
Year: 2019
Month: December
Day: 14
Publisher: NeurIPS

Department(s): Empirical Inference
Bibtex Type: Conference Paper (conference)
Paper Type: Conference

Event Name: NeurIPS 2019 Workshop Do the right thing: machine learning and causal inference for improved decision making
Event Place: Vancouver, CA

State: Published
URL: http://tripods.cis.cornell.edu/neurips19_causalml/

Links: arXiv
Attachments: Poster

BibTex

@conference{KueRubSchWel19,
  title = {Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks},
  author = {von K{\"u}gelgen, J. and Rubenstein, P. K. and Sch{\"o}lkopf, B. and Weller, A.},
  booktitle = {NeurIPS 2019 Workshop Do the right thing: machine learning and causal inference for improved decision making},
  publisher = {NeurIPS},
  month = dec,
  year = {2019},
  url = {http://tripods.cis.cornell.edu/neurips19_causalml/},
  month_numeric = {12}
}