Eberhardt, Frederick
- Chalupka, Krzysztof and Bischoff, Tobias, et el. (2016) Unsupervised Discovery of El Niño Using Causal Feature Learning on Microlevel Climate Data; ISBN 978-0-9966431-1-5; Uncertainty in Artificial Intelligence. Proceedings of the Thirty-Second Conference (2016); 72-81; 10.48550/arXiv.1605.09370
- Chalupka, Krzysztof and Perona, Pietro, et el. (2015) Visual Causal Feature Learning; ISBN 978-0-9966431-0-8; UAI'15 Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence; 181-190; 10.48550/arXiv.1412.2309
- Hyttinen, Antti and Hoyer, Patrik O., et el. (2013) Discovering cyclic causal models with latent variables: a general SAT-based procedure; ISBN 9780974903996; UAI'13 Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence; 301-310; 10.48550/arXiv.1309.6836
- Hyttinen, Antti and Eberhardt, Frederick, et el. (2012) Causal discovery of linear cyclic models from multiple experimental data sets with overlapping variables; ISBN 978-0-9749039-8-9; UAI'12 Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence; 387-396; 10.48550/arXiv.1210.4879
- Eberhardt, Frederick and Glymour, Clark, et el. (2012) On the number of experiments sufficient and in the worst case necessary to identify all causal relations among N variables; ISBN 0-9749039-1-4; UAI'05 Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence; 178-184; 10.48550/arXiv.1207.1389
- Hyttinen, Antti and Eberhardt, Frederick, et el. (2011) Noisy-OR Models with Latent Confounding; ISBN 978-0-9749039-7-2; UAI'11 Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence; 363-372; 10.48550/arXiv.1202.3735v1
- Eberhardt, Frederick (2008) Almost Optimal Intervention Sets for Causal Discovery; ISBN 0-9749039-4-9; UAI'08 Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence; 161-168; 10.48550/arXiv.1206.3250