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 |
Department(s): | Empirical Inference |
Bibtex Type: | Conference Paper (conference) |
Paper Type: | Conference |
Event Place: | Vancouver, CA |
State: | Published |
URL: | http://tripods.cis.cornell.edu/neurips19_causalml/ |
Links: |
arXiv
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Attachments: |
Poster
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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}, month = dec, year = {2019}, doi = {}, url = {http://tripods.cis.cornell.edu/neurips19_causalml/}, month_numeric = {12} } |