Empirical Inference
Conference Paper
2019
Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks
| 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 |
| Bibtex Type: | Conference Paper (conference) |
| Event Place: | Vancouver, CA |
| State: | Published |
| URL: | http://tripods.cis.cornell.edu/neurips19_causalml/ |
| Electronic Archiving: | grant_archive |
| Links: | |
| Attachments: | |
BibTex
@conference{KueRubSchWel19,
title = {Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks},
booktitle = {NeurIPS 2019 Workshop Do the right thing: machine learning and causal inference for improved decision making},
month = dec,
year = {2019},
slug = {kuerubschwel19},
author = {von K{\"u}gelgen, J. and Rubenstein, P. K. and Sch{\"o}lkopf, B. and Weller, A.},
url = {http://tripods.cis.cornell.edu/neurips19_causalml/},
month_numeric = {12}
}