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Emilija Perković
Emilija Perković
Assistant Professor, Department of Statistics, University of Washington
Bestätigte E-Mail-Adresse bei uw.edu
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Zitiert von
Zitiert von
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Complete graphical characterization and construction of adjustment sets in Markov equivalence classes of ancestral graphs
E Perkovic, J Textor, M Kalisch, MH Maathuis
The Journal of Machine Learning Research 18 (1), 8132-8193, 2018
1062018
Graphical criteria for efficient total effect estimation via adjustment in causal linear models
L Henckel, E Perković, MH Maathuis
Journal of the Royal Statistical Society: Series B 84 (2), 579-599, 2022
852022
A complete generalized adjustment criterion
E Perković, J Textor, M Kalisch, MH Maathuis
Uncertainty in Artificial Intelligence 2015, 2015
742015
Interpreting and using CPDAGs with background knowledge
E Perković, M Kalisch, MH Maathuis
Uncertainty in Artificial Intelligence 2017, 2017
522017
Identifying causal effects in maximally oriented partially directed acyclic graphs
E Perković
Uncertainty in Artificial Intelligence 2020, 2020
262020
Efficient least squares for estimating total effects under linearity and causal sufficiency
FR Guo, E Perković
Journal of Machine Learning Research 23 (104), 1-41, 2022
142022
Minimal enumeration of all possible total effects in a Markov equivalence class
R Guo, E Perkovic
International Conference on Artificial Intelligence and Statistics, 2395-2403, 2021
142021
pcalg: Methods for graphical models and causal inference
M Kalisch, A Hauser, M Maechler, D Colombo, D Entner, P Hoyer, ...
R Package retrieved from https://CRAN. R-project. org/package= pcalg, 2021
72021
Graphical characterizations of adjustment sets
E Perković
ETH Zurich, 2018
52018
Package ‘pcalg’
M Kalisch, A Hauser, M Maechler, D Colombo, D Entner, P Hoyer, ...
42024
Variable elimination, graph reduction and the efficient g-formula
FR Guo, E Perković, A Rotnitzky
Biometrika 110 (3), 739-761, 2023
32023
Conditional Adjustment in a Markov Equivalence Class
S LaPlante, E Perković
arXiv preprint arXiv:2311.06458, 2023
2023
Leadership in Statistics and Data Science: Planning for Inclusive Excellence, by Amanda L. Golbeck, ed. Cham, Switzerland, Springer, 2021, xxvii+ 432 pp., $159.99 (H), ISBN …
E Perković
The American Statistician 76 (3), 306-307, 2022
2022
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