I am working in the area of causal inference, specifically inferring causal relations in case where only observational data is available. My interests include identifying finite latent common causes of some observed variables based on their joint probability distribution. I am part of the Causal Inference Group.
ei
Sgouritsa, E.
Causal Discovery Beyond Conditional Independences
University of Tübingen, Germany, October 2015 (phdthesis)
ei
pn
Sgouritsa, E., Janzing, D., Hennig, P., Schölkopf, B.
Inference of Cause and Effect with Unsupervised Inverse Regression
In Proceedings of the 18th International Conference on Artificial Intelligence and Statistics, 38, pages: 847-855, JMLR Workshop and Conference Proceedings, (Editors: Lebanon, G. and Vishwanathan, S.V.N.), JMLR.org, AISTATS, 2015 (inproceedings)
ei
Kpotufe, S., Sgouritsa, E., Janzing, D., Schölkopf, B.
Consistency of Causal Inference under the Additive Noise Model
In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 478-495, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)
ei
Schölkopf, B., Janzing, D., Peters, J., Sgouritsa, E., Zhang, K., Mooij, J.
Semi-supervised learning in causal and anticausal settings
In Empirical Inference, pages: 129-141, 13, Festschrift in Honor of Vladimir Vapnik, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)
ei
Sgouritsa, E., Janzing, D., Peters, J., Schölkopf, B.
Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders
In Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (UAI), pages: 556-565, (Editors: A Nicholson and P Smyth), AUAI Press Corvallis, Oregon, USA, UAI, 2013 (inproceedings)
ei
Schölkopf, B., Janzing, D., Peters, J., Sgouritsa, E., Zhang, K., Mooij, J.
On Causal and Anticausal Learning
In Proceedings of the 29th International Conference on Machine Learning, pages: 1255-1262, (Editors: J Langford and J Pineau), Omnipress, New York, NY, USA, ICML, 2012 (inproceedings)
ei
Janzing, D., Sgouritsa, E., Stegle, O., Peters, J., Schölkopf, B.
Detecting low-complexity unobserved causes
In pages: 383-391, (Editors: FG Cozman and A Pfeffer), AUAI Press, Corvallis, OR, USA, 27th Conference on Uncertainty in Artificial Intelligence (UAI), July 2011 (inproceedings)
For website questions and technical problems please contact:
© 2018 Max-Planck-Gesellschaft - Imprint | Privacy Policy
