Eberhardt, Frederick
Eberhardt, Frederick (2022) A contemporary example of Reichenbachian coordination ; Synthese; Vol. 200; No. 2; Art. No. 90; 10.1007/s11229-022-03571-8
Eberhardt, Frederick and Lee, Lin-Lin (2022) Causal Emergence: When Distortions in a Map Obscure the Territory ; Philosophies; Vol. 7; No. 2; Art. No. 30; 10.3390/philosophies7020030
Thompson, W. H. and Esteban, O., et el. (2021) Intracranial electrical stimulation alters meso-scale network integration as a function of network topology ; 10.1101/2021.01.16.426941
Dubois, Julien and Eberhardt, Frederick, et el. (2020) Personality beyond taxonomy ; Nature Human Behaviour; Vol. 4; No. 11; 1110-1117; 10.1038/s41562-020-00989-3
Dubois, Julien and Oya, Hiroyuki, et el. (2020) Causal Mapping of Emotion Networks in the Human Brain: Framework and Initial Findings ; Neuropsychologia; Vol. 145; Art. No. 106571; PMCID PMC5949245; 10.1016/j.neuropsychologia.2017.11.015
Zhalama, Mr. and Zhang, Jiji, et el. (2020) ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions ; 10.48550/arXiv.1906.02385
Beckers, Sander and Eberhardt, Frederick, et el. (2019) Approximate Causal Abstraction ; Proceedings of Machine Learning Research; Vol. 115; 606-615; 10.48550/arXiv.1906.11583
Chalupka, Krzysztof and Eberhardt, Frederick, et el. (2019) Estimating Causal Direction and Confounding of Two Discrete Variables ; 10.48550/arXiv.1611.01504
Chalupka, Krzysztof and Perona, Pietro, et el. (2018) Fast Conditional Independence Test for Vector Variables with Large Sample Sizes ; 10.48550/arXiv.1804.02747
Hyttinen, Antti and Plis, Sergey, et el. (2017) A constraint optimization approach to causal discovery from subsampled time series data ; International Journal of Approximate Reasoning; Vol. 90; 208-225; 10.1016/j.ijar.2017.07.009
Chalupka, Krzysztof and Eberhardt, Frederick, et el. (2017) Causal Feature Learning: An Overview ; Behaviormetrika; Vol. 44; No. 1; 137-164; 10.1007/s41237-016-0008-2
Hyttinen, Antti and Plis, Sergey, et el. (2016) Causal Discovery from Subsampled Time Series Data by Constraint Optimization ; Proceedings of Machine Learning Research; Vol. 52; 216-227; PMCID PMC5305170; 10.48550/arXiv.arXiv.1602.07970
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. (2016) Multi-Level Cause-Effect Systems ; Proceedings of Machine Learning Research; Vol. 51; 361-369; 10.48550/arXiv.1512.07942
Eberhardt, Frederick (2016) Green and grue causal variables ; Synthese; Vol. 193; No. 4; 1029-1046; 10.1007/s11229-015-0832-z
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
Abrams, Marshall and Eberhardt, Frederick, et el. (2015) Equidynamics and reliable reasoning about frequencies ; Metascience; Vol. 24; No. 2; 173-188; 10.1007/s11016-014-9971-y
Eberhardt, Frederick (2014) Direct Causes and the Trouble with Soft Interventions ; Erkenntnis; Vol. 79; No. 4; 755-777; 10.1007/s10670-013-9552-2
Eberhardt, Frederick (2013) Experimental Indistinguishability of Causal Structures ; Philosophy of Science; Vol. 80; No. 5; 684-696; 10.1086/673865
Hyttinen, Antti and Eberhardt, Frederick, et el. (2013) Experiment Selection for Causal Discovery ; Journal of Machine Learning Research; Vol. 14; 3041-3071
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
