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Jonas Peters
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Publications
- 2016
- [j7]Joris M. Mooij, Jonas Peters, Dominik Janzing, Jakob Zscheischler, Bernhard Schölkopf:
Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks. J. Mach. Learn. Res. 17: 32:1-32:102 (2016) - [j6]Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters:
Modeling confounding by half-sibling regression. Proc. Natl. Acad. Sci. USA 113(27): 7391-7398 (2016) - 2015
- [c15]Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters:
Removing systematic errors for exoplanet search via latent causes. ICML 2015: 2218-2226 - [i11]Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters:
Removing systematic errors for exoplanet search via latent causes. CoRR abs/1505.03036 (2015) - 2014
- [j3]Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf:
Causal discovery with continuous additive noise models. J. Mach. Learn. Res. 15(1): 2009-2053 (2014) - [e1]Joris M. Mooij, Dominik Janzing, Jonas Peters, Tom Claassen, Antti Hyttinen:
Proceedings of the UAI 2014 Workshop Causal Inference: Learning and Prediction co-located with 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014), Quebec City, Canada, July 27, 2014. CEUR Workshop Proceedings 1274, CEUR-WS.org 2014 [contents] - [i10]Joris M. Mooij, Jonas Peters, Dominik Janzing, Jakob Zscheischler, Bernhard Schölkopf:
Distinguishing cause from effect using observational data: methods and benchmarks. CoRR abs/1412.3773 (2014) - 2013
- [c13]Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij:
Semi-supervised Learning in Causal and Anticausal Settings. Empirical Inference 2013: 129-141 - [c12]Jonas Peters, Dominik Janzing, Bernhard Schölkopf:
Causal Inference on Time Series using Restricted Structural Equation Models. NIPS 2013: 154-162 - [c11]Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schölkopf:
Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders. UAI 2013 - [i9]Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schölkopf:
Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders. CoRR abs/1309.6860 (2013) - 2012
- [c10]Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij:
On causal and anticausal learning. ICML 2012 - [i7]Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf:
Detecting low-complexity unobserved causes. CoRR abs/1202.3737 (2012) - [i6]Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf:
Identifiability of Causal Graphs using Functional Models. CoRR abs/1202.3757 (2012) - [i5]Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf:
Kernel-based Conditional Independence Test and Application in Causal Discovery. CoRR abs/1202.3775 (2012) - [i4]Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf:
Identifying confounders using additive noise models. CoRR abs/1205.2640 (2012) - [i3]Jonas Peters, Dominik Janzing, Bernhard Schölkopf:
Causal Inference on Time Series using Structural Equation Models. CoRR abs/1207.5136 (2012) - 2011
- [j1]Jonas Peters, Dominik Janzing, Bernhard Schölkopf:
Causal Inference on Discrete Data Using Additive Noise Models. IEEE Trans. Pattern Anal. Mach. Intell. 33(12): 2436-2450 (2011) - [c9]Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf:
Detecting low-complexity unobserved causes. UAI 2011: 383-391 - [c8]Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf:
Identifiability of Causal Graphs using Functional Models. UAI 2011: 589-598 - [c7]Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf:
Kernel-based Conditional Independence Test and Application in Causal Discovery. UAI 2011: 804-813 - [i1]Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Kun Zhang:
Robust Learning via Cause-Effect Models. CoRR abs/1112.2738 (2011) - 2010
- [c6]Jonas Peters, Dominik Janzing, Bernhard Schölkopf:
Identifying Cause and Effect on Discrete Data using Additive Noise Models. AISTATS 2010: 597-604 - 2009
- [c5]Joris M. Mooij, Dominik Janzing, Jonas Peters, Bernhard Schölkopf:
Regression by dependence minimization and its application to causal inference in additive noise models. ICML 2009: 745-752 - [c4]Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf:
Detecting the direction of causal time series. ICML 2009: 801-808 - [c3]Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf:
Identifying confounders using additive noise models. UAI 2009: 249-257 - 2008
- [c2]Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf:
Kernel Methods for Detecting the Direction of Time Series. GfKl 2008: 57-66 - [c1]Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf:
Nonlinear causal discovery with additive noise models. NIPS 2008: 689-696
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