Jonas Peters (bib-file) [Peters2014neco]@article{Peters2014neco, author = {J.~Peters and P.~B\"uhlmann},
 title = {Structural Intervention Distance ({SID}) for Evaluating Causal Graphs},
 journal = {Neural Computation (to appear), ArXiv e-prints (1306.1043)},
 year = {2013},
 } 

[Peters2014jci]@article{Peters2014jci,
 author = {J.~Peters},
 year = {2014},
 title = {On the Intersection Property of Conditional Independence and its Application to Causal Discovery},
 journal = {Journal of Causal Inference (to appear), ArXiv e-prints (1403.0408)},
 } 

[Buhlmann2014annals]@article{Buhlmann2014annals,
 author = {P.~{B{\"u}hlmann} and J.~Peters and J.~Ernest},
 title = {{CAM}: Causal Additive Models, high-dimensional order search and penalized regression},
 journal = {Annals of Statistics}, 
 volume = {42},
 pages = {2526--2556},
 year = {2014}
 } 

[Peters2014jmlr]@article{Peters2014jmlr,
 author = {J.~Peters and J.M.~Mooij and D.~Janzing and B.~Sch\"olkopf},
 title = {Causal Discovery with Continuous Additive Noise Models}, 
 year = {2014},
 journal = {Journal of Machine Learning Research},
 volume = {15},
 pages = {2009--2053}
 } 
 
 [Peters2014biometrika]@article{Peters2014biometrika,
 author = {J.~Peters and P.~B{\"u}hlmann},
 title = {Identifiability of {G}aussian Structural Equation Models with Equal Error Variances},
 journal = {Biometrika},
 pages = {219--228},
 volume = {101},
 year = {2014}
 }
 
 [Peters2014nips]@article{Peters2013nips,
 author = {J.~Peters and D.~Janzing and B.~Sch\"olkopf},
 title = {Causal Inference on Time Series using Structural Equation Models},
 booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems 25 ({NIPS})}, 
 pages = {585--592},
 year = {2013}
 }
 % publisher = {MIT Press}
 
 [Bottou2013jmlr]@article{Bottou2013jmlr,
 author = {L.~Bottou and J.~Peters and J.~Qui{\~n}onero-Candela and D.~X.~Charles and D.~M.~Chickering and E.~Portugualy and D.~Ray and P.~Simard and E.~Snelson},
 title = {Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising},
 journal = {Journal of Machine Learning Research},
 volume = {14},
 pages = {3207--3260},
 year = {2013}
 }
 
 [Sgouritsa2013uai]@inproceedings{Sgouritsa2013uai,
 author = {E.~Sgouritsa and D.~Janzing and J.~Peters and B.~Sch\"{o}lkopf},
 title = {Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders},
 booktitle = {Proceedings of the 29th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI})},
 pages = {556--565},
 year = {2013}
 }
 % publisher = {AUAI Press},
 % address = {Corvallis, Oregon, USA},
 
 [Peters2012phd]@PhDThesis{Peters2012phd,
 author = {J.~Peters}, 
 title = {Restricted Structural Equation Models for Causal Inference},
 School = {ETH Zurich and MPI for Intelligent Systems},
 year = {2012},
 note = {\url{http://dx.doi.org/10.3929/ethz-a-007597940}}
 }
 
 [Schoelkopf2012icml]@inproceedings{Schoelkopf2012icml,
 author = {B.~Sch\"{o}lkopf and D.~Janzing and J.~Peters and E.~Sgouritsa and K.~Zhang and J.M.~Mooij},
 booktitle = {Proceedings of the 29th International Conference on Machine Learning ({ICML})},
 title = {On causal and anticausal learning},
 pages = {1255--1262},
 year = {2012}
 }
 % editor = {John Langford and Joelle Pineau},
 % publisher = {Omnipress},
 % address = {New York, NY, USA},
 [Zhang2011uai]@inproceedings{Zhang2011uai,
 author = {K.~Zhang and J.~Peters and D.~Janzing and B.~Sch{\"o}lkopf},
 title = {Kernel-based Conditional Independence Test and Application in Causal Discovery},
 booktitle = {Proceedings of the 27th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI})},
 pages = {804--813},
 year = {2011}
 }
 % publisher = {AUAI Press},
 % address = {Corvallis, Oregon, USA},
 
 [Peters2011uai]@inproceedings{Peters2011uai,
 author = {J.~Peters and J.M.~Mooij and D.~Janzing and B.~Sch\"{o}lkopf},
 title = {Identifiability of Causal Graphs using Functional Models},
 booktitle = {Proceedings of the 27th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI})},
 pages = {589--598},
 year = {2011}
 }
 % publisher = {AUAI Press},
 % address = {Corvallis, Oregon, USA},
 
 [Janzing2011uai]@inproceedings{Janzing2011uai,
 author = {D.~Janzing and E.~Sgouritsa and O.~Stegle and J.~Peters and B.~Sch\"{o}lkopf},
 title = {Detecting low-complexity unobserved causes},
 booktitle = {Proceedings of the 27th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI})},
 pages = {383--391},
 year = {2011}
 }
 % publisher = {AUAI Press},
 % address = {Corvallis, Oregon, USA},
 
 [Peters2011tpami]@article{Peters2011tpami,
 author = {J.~Peters and D.~Janzing and B.~Sch\"{o}lkopf},
 title = {Causal Inference on Discrete Data Using Additive Noise Models},
 journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
 volume = {33},
 year = {2011},
 pages = {2436-2450},
 publisher = {IEEE Computer Society}
 }
 %address = {Los Alamitos, CA, USA},
 %doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2011.71},
 
 [Peters2010aistats]@article{Peters2010aistats,
 author = {J.~Peters and D.~Janzing and B.~Sch\"{o}lkopf},
 title = {Identifying Cause and Effect on Discrete Data using Additive Noise Models},
 booktitle = {AIStats 13},
 publisher = {Journal of Machine Learning Research: Workshop and Conference Proceedings},
 volume = {9},
 year = {2010},
 pages = {597--604}
 }
 
 [Janzing2009uai]@inproceedings{Janzing2009uai,
 title = {Identifying confounders using additive noise models},
 author = {D.~Janzing and J.~Peters and J.M.~Mooij and B.~Sch\"{o}lkopf},
 booktitle = {Proceedings of the 25th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI} )},
 pages = {249--257},
 year = {2009}
 }
 % publisher = {AUAI Press},
 % address = {Corvallis, Oregon, USA},
 
 [Peters2009icml]@inproceedings{Peters2009icml,
 author = {J.~Peters and D.~Janzing and A.~Gretton and B.~Sch\"olkopf},
 title = {Detecting the Direction of Causal Time Series},
 booktitle = {Proceedings of the 26th International Conference on Machine Learning ({ICML})},
 pages = {801--808},
 year = {2009},
 }
 
 [Mooij2009icml]@inproceedings{Mooij2009icml,
 author = {J.M.~Mooij and D.~Janzing and J.~Peters and B.~Sch\"{o}lkopf},
 booktitle = {Proceedings of the 26th International Conference on Machine Learning ({ICML})},
 pages = {745--752},
 title = {Regression by Dependence Minimization and its Application to Causal Inference},
 year = {2009}
 }
 
 [Hoyer2009nips]@inproceedings{Hoyer2009nips,
 author = {P.O.~Hoyer and D.~Janzing and J.M.~Mooij and J.~Peters and B.~Sch\"olkopf},
 title = {Nonlinear causal discovery with additive noise models},
 booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems 21 ({NIPS})},
 pages = {689--696},
 year = {2009}
 }
 %publisher = {MIT Press},
 [Peters2009gfkl]@inproceedings{Peters2009gfkl,
 author = {J.~Peters and D.~Janzing and A.~Gretton and B.~Sch{\"o}lkopf},
 title = {Kernel methods for detecting the direction of time series},
 booktitle = {Proccedings of the 32nd Annual Conference of the German Classification Society (GfKl 2008)},
 year = {2009},
 pages = {1--10}
 }
 
 [Peters2008diploma]@misc{Peters2008diploma,
 author = {J.~Peters}, 
 title = {Asymmetries of Time Series under Inverting their Direction},
 howpublished = {Diploma Thesis, University of Heidelberg},
 year = {2008},
 note = {\url{http://stat.ethz.ch/people/jopeters}}
 }