@article{Bongers++_AOS_21,
  author = {Stephan Bongers and Patrick Forr{\'e} and Jonas Peters and Joris M. Mooij},
  title = {Foundations of Structural Causal Models with Cycles and Latent Variables},
  journal = {Annals of Statistics},
  year = {2021},
  volume = {49},
  number = {5},
  pages = {2885-2915},
  doi = {10.1214/21-AOS2064},
}

@article{Chickering2002,
  title={Optimal structure identification with greedy search},
  author={Chickering, David Maxwell},
  journal={Journal of machine learning research},
  volume={3},
  number={Nov},
  pages={507--554},
  year={2002}
}

@inproceedings{Claassen2011,
  title={A logical characterization of constraint-based causal discovery},
  author={Claassen, Tom and Heskes, Tom},
  booktitle={Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence},
  pages={135--144},
  year={2011}
}
@inproceedings{ClaassenB2022,
  title={Greedy equivalence search in the presence of latent confounders},
  author={Claassen, Tom and Bucur, Ioan G},
  booktitle={Uncertainty in Artificial Intelligence},
  pages={443--452},
  year={2022},
  organization={PMLR}
}

@inproceedings{Dawid2010,
  title={Beware of the DAG!},
  author={Dawid, A Philip},
  booktitle={Causality: objectives and assessment},
  pages={59--86},
  year={2010},
  organization={PMLR}
}

@article{ForreMooij_1710.08775,
  author = "Patrick Forr{\'e} and Joris M. Mooij",
  journal = "arXiv.org preprint",
  title = "Markov Properties for Graphical Models with Cycles and Latent Variables",
  volume = "arXiv:1710.08775 [math.ST]",
  year = 2017,
  month = Oct,
  url = "https://arxiv.org/abs/1710.08775",
}

@inproceedings{ForreM2018,
  title     = {Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders},
  author    = {Patrick Forr{\'e} and Joris M. Mooij},
  booktitle = {Proceedings of the 34th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-18)},
  year      = 2018,
}

@inproceedings{HuE2020,
  title={Faster algorithms for Markov equivalence},
  author={Hu, Zhongyi and Evans, Robin},
  booktitle={Conference on Uncertainty in Artificial Intelligence},
  pages={739--748},
  year={2020},
  organization={PMLR}
}

@article {HyttinenEH2012,
    AUTHOR = {Hyttinen, A. and Eberhardt, F. and Hoyer, P.O.},
     TITLE = {Learning linear cyclic causal models with latent variables},
   JOURNAL = {Journal of Machine Learning Research},
    VOLUME = {13},
      YEAR = {2012},
     PAGES = {3387--3439}
}

@book{KollerF2009,
  title={Probabilistic graphical models: principles and techniques},
  author={Koller, Daphne and Friedman, Nir},
  year={2009},
  publisher={MIT press}
}

@article{Kos96,
  author = {J.T.A. Koster},
  title = {{M}arkov Properties of Nonrecursive Causal Models},
  journal = {The Annals of Statistics},
  publisher = {Institute of Mathematical Statistics},
  volume =  24,
  number = 5,
  pages = {2148--2177},
  year = 1996
}

@inproceedings{LacerdaSRH2008,
  title     = {Discovering cyclic causal models by Independent Components Analysis},
  author    = {Gustavo Lacerda and Peter Spirtes and Joseph Ramsey and Patrik O. Hoyer},
  booktitle = {Proceedings of the 24th Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-08)},
  year      = 2008
}

@inproceedings{MooijHeskes_UAI_13,
  title     = {Cyclic Causal Discovery from Continuous Equilibrium Data},
  author    = {Joris M. Mooij and Tom Heskes},
  booktitle = {Proceedings of the 29th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-13)},
  year      = 2013,
  location  = {Corvallis, Oregon},
  publisher = {AUAI Press},
  editor    = {Ann Nicholson and Padhraic Smyth},
  pages     = {431--439},
  url       = {http://auai.org/uai2013/prints/papers/23.pdf}
}

@inproceedings{Mooij_et_al_NIPS_11,
  author    = {Joris M. Mooij and Dominik Janzing and Tom Heskes and Bernhard Sch{\"o}lkopf},
  title     = {On Causal Discovery with Cyclic Additive Noise Models},
  booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems 24 ({NIPS}*2011)},
  editor    = {J. Shawe-Taylor and R.S. Zemel and P. Bartlett and F.C.N. Pereira and K.Q. Weinberger},
  pages     = {639--647},
  year      = {2011},
  url       = {http://books.nips.cc/papers/files/nips24/NIPS2011_0449.pdf}
}

@inproceedings{MooijC2020,
  title={Constraint-based causal discovery using partial ancestral graphs in the presence of cycles},
  author={Mooij, Joris M and Claassen, Tom},
  booktitle={Conference on Uncertainty in Artificial Intelligence},
  pages={1159--1168},
  year={2020},
  organization={PMLR}
}

@article{Nea00,
  author = {R.M. Neal},
  title = {On Deducing Conditional Independence from $d$-Separation in Causal Graphs with Feedback},
  journal = {Journal of Artificial Intelligence Research},
  volume = 12,
  pages = {87--91},
  year = 2000,
  url = {https://www.jair.org/index.php/jair/article/download/10250/24409}
}

@inproceedings{PearlD1996,
  author = {J. Pearl and R. Dechter},
  title = {Identifying Independence in Causal Graphs with Feedback},
  booktitle = {Proceedings of the 12th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-96)},
  year = {1996},
  pages = {420-426}
}

@Book{Pearl2009,
author =         {Judea Pearl},
title =          {Causality: Models, Reasoning and Inference},
year =   {2009},
publisher =      {Cambridge University Press},
address =        {}
}

@inproceedings{Richardson1996a_CCD,
  title={A discovery algorithm for directed cyclic graphs},
  author={Richardson, Thomas},
  booktitle={Proceedings of the Twelfth international conference on Uncertainty in Artificial Intelligence ({UAI}-96)},
  pages={454--461},
  year={1996}
}

@inproceedings{Richardson1996b_MEC,
  title={A polynomial-time algorithm for deciding {M}arkov equivalence of directed cyclic graphical models},
  author={Richardson, Thomas},
  booktitle={Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence},
  pages={462--469},
  year={1996}
}

@techreport{Richardson1996c_DCCS,
  title={Discovering Cyclic Causal Structure},
  author={Richardson, Thomas},
 number = {CMU-PHIL-68},
 institution = {Carnegie Mellon University},
 year={1996}
}

@article{Richardson1997,
  title={A characterization of {M}arkov equivalence for directed cyclic graphs},
  author={Richardson, Thomas},
  journal={International Journal of Approximate Reasoning},
  volume={17},
  number={2-3},
  pages={107--162},
  year={1997},
  publisher={Elsevier}
}

@InCollection{RichardsonS1999,
  author = {Richardson, T. and Spirtes, P.},
  title = {Automated discovery of linear feedback models},
  booktitle = 	 {Computation, Causation, and Discovery},
  publisher =    {MIT Press},
  year = 	 {1999},
  pages =        {253--304}
}


@article{RichardsonS2002,
author = "Thomas S. Richardson and Peter Spirtes",
journal = "The Annals of Statistics",
month = Aug,
number = "4",
pages = "962--1030",
title = "Ancestral graph {M}arkov models",
volume = "30",
year = "2002"
}

@article{Robins2003,
  title={Semantics of causal DAG models and the identification of direct and indirect effects},
  author={Robins, James M},
  journal={Oxford Statistical Science Series},
  pages={70--82},
  year={2003},
  publisher={OXFORD UNIV PRESS}
}

@inproceedings{RothenhauslerHPM2015,
title = {{BACKSHIFT}: Learning causal cyclic graphs from unknown shift interventions},
author = {Rothenh\"{a}usler, D. and Heinze, C. and Peters, J. and Meinshausen, N.},
booktitle = {Advances in Neural Information Processing Systems 28 ({NIPS} 2015)},
pages = {1513--1521},
year = {2015}
}

@techreport{Spirtes1994,
author = {P. Spirtes},
year = {1994},
title = {Conditional Independence in Directed Cyclic Graphical Models for Feedback},
number = {CMU-PHIL-54},
institution = {Carnegie Mellon University}
}

@inproceedings{Spirtes1995,
  title = {Directed Cyclic Graphical Representations of Feedback Models},
  author = {P. Spirtes},
  booktitle = {Proceedings of the Eleventh Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-95)},
  pages = {499--506},
  year = {1995},
}

@book{SGS2000,
  author = {Spirtes, Peter and Glymour, Clark and Scheines, Richard},
  edition = {2nd},
  publisher = {MIT press},
  title = {Causation, Prediction, and Search},
  year = {2000}
}

@article{Strobl2018,
author="Strobl, Eric V.",
title="A constraint-based algorithm for causal discovery with cycles, latent variables and selection bias",
journal="International Journal of Data Science and Analytics",
year="2018",
volume=8,
pages={33-56},
}

@article{Tarjan1972,
  title={Depth-first search and linear graph algorithms},
  author={Tarjan, Robert},
  journal={SIAM journal on computing},
  volume={1},
  number={2},
  pages={146--160},
  year={1972},
  publisher={SIAM}
}

@inproceedings{WienobstBL2022,
  title={A new constructive criterion for Markov equivalence of MAGs},
  author={Wien{\"o}bst, Marcel and Bannach, Max and Li{\'s}kiewicz, Maciej},
  booktitle={Uncertainty in Artificial Intelligence},
  pages={2107--2116},
  year={2022},
  organization={PMLR}
}

@article{Wright1921,
  author = {S. Wright},
  title = {Correlation and Causation},
  journal = {Journal of Agricultural Research},
  pages = {557--585},
  volume = {20},
  year = {1921}
}

@article{Zhang2008,
 author = {Zhang, Jiji},
 title = {On the Completeness of Orientation Rules for Causal Discovery in the Presence of Latent Confounders and Selection Bias},
 journal = {Artificial Intelligence},
 volume = {172},
 number = {16-17},
 pages     = {1873--1896},
 year = {2008},
} 


%===
@inproceedings{LSR08,
  title     = {Discovering cyclic causal models by Independent Components Analysis},
  author    = {Gustavo Lacerda and Peter Spirtes and Joseph Ramsey and Patrik O. Hoyer},
  booktitle = {Proceedings of the 24th Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-08)},
  year      = 2008
}

@inproceedings{Meek1995PC,
  author = {Christopher Meek},
  title = {Causal inference and causal explanation with background knowledge},
  booktitle = {Proceedings of the 11th Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-95)},
  year = 1995,
  pages = {403-411},
}

@inproceedings{Ali++2005,
  author = {R. Ayesha Ali and Thomas S. Richardson and Peter Spirtes and Jiji Zhang},
  title = {Towards Characterizing {M}arkov Equivalence Classes for Directed Acyclic Graphs with Latent Variables},
  booktitle = {Proceedings of the 21th Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-05)},
  year = 2005,
  pages = {10-17},
}

@phdthesis{RichardsonPhD1996,
  author = {Thomas S. Richardson},
  title={Models of Feedback: Interpretation and Discovery},
  school={Carnegie-Mellon University},
  year={1996}
}

@techreport{SpirtesVerma92,
author = {Peter Spirtes and Thomas Verma},
year = 1992,
title = {Equivalence of Causal Models with Latent Variables},
number = {CMU-PHIL-33},
institution = {Carnegie Mellon University}
}

@phdthesis{ManiPhD2006,
month = {March},
title = {A Bayesian Local Causal Discovery Framework},
author = {Subramani Mani},
year = {2006},
school = {University of Pittsburg},
url = {http://d-scholarship.pitt.edu/10181/},
}

@article{ICP2016,
  title = {Causal inference using invariant prediction: identification and confidence intervals},
  author = {Peters, Jonas and B{\"u}hlmann, Peter and Meinshausen, Nicolai},
  journal = {Journal of the Royal Statistical Society, Series B},
  volume = {78},
number = {5},
pages = {947--1012},
  year = {2016},
}

@article{Cooper1997,
 author = {Cooper, Gregory F.},
 title = {A Simple Constraint-Based Algorithm for Efficiently Mining Observational Databases for Causal Relationships},
 journal = {Data Mining and Knowledge Discovery},
 volume = {1},
 number = {2},
 year = {1997},
  pages = {203--224},
} 

@article{Bongers++_1611.06221v3,
  author = "Stephan Bongers and Patrick Forr{\'e} and Jonas Peters and Bernhard Sch{\"o}lkopf and Joris M. Mooij",
  journal = "arXiv.org preprint",
  title = "Foundations of Structural Causal Models with Cycles and Latent Variables",
  volume = "arXiv:1611.06221v3 [stat.ME]",
  year = 2020,
  url = "https://arxiv.org/abs/1611.06221v3"
}

@article{Ali++2009,
  journal = {The Annals of Statistics},
  year = 2009,
  volume = 37,
  number = {5B},
  pages = {2808-2837},
  title = {Markov Equivalence For Ancestral Graphs},
  author = {R. Ayesha Ali and Thomas S. Richardson and Peter Spirtes}
}

@article{Colombo++2012,
  journal = {The Annals of Statistics},
  year = 2012,
  volume = 40, 
  number = 1, 
  pages = {294--321},
  title = {Learning High-Dimensional Directed Acyclic Graphs with Latent and Selection Variables},
  author = {Diego Colombo and Marloes H. Maathuis and Markus Kalisch and Thomas S. Richardson}
}

@inproceedings{ClaassenMooijHeskes_UAI_13,
  title     = {Learning Sparse Causal Models is not {NP}-hard},
  author    = {Tom Claassen and Joris M. Mooij and Tom Heskes},
  booktitle = {Proceedings of the 29th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-13)},
  year      = 2013,
  pages     = {172--181},
  url       = {http://auai.org/uai2013/prints/papers/121.pdf}
}
%  location  = {Corvallis, Oregon},
%  publisher = {AUAI Press},
%  editor    = {Ann Nicholson and Padhraic Smyth},

@incollection{SMR1999,
author = {Peter Spirtes and Christopher Meek and Thomas S. Richardson},
year = 1999,
title = {An Algorithm for Causal Inference in the Presence of Latent Variables and Selection Bias},
booktitle = {Computation, Causation and Discovery},
pages = {211-252},
chapter = 6,
publisher = {The MIT Press}
}
%editor = {Clark Glymour and Gregory F. Cooper},

@inproceedings{SMR1995,
  author = {Peter Spirtes and Christopher Meek and Thomas S. Richardson},
  year = 1995,
  title = {Causal inference in the presence of latent variables and selection bias},
  booktitle = {Proceedings of the 11th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI-95})},
  pages = {499-506},
}
% location = {San Francisco},
% publisher = {Morgan Kaufmann}

@article{BongersMooij_1803.08784,
  author = "Stephan Bongers and Joris M. Mooij",
  journal = "arXiv.org preprint",
  title = "From Random Differential Equations to Structural Causal Models: the stochastic case",
  volume = "arXiv:1803.08784v2 [cs.AI]",
  year = 2018,
  month = Mar,
  url = "https://arxiv.org/abs/1803.08784v2",
}

@inproceedings{Rothenhausler_15,
title = {{BACKSHIFT}: Learning causal cyclic graphs from unknown shift interventions},
author = {Rothenh\"{a}usler, D. and Heinze, C. and Peters, J. and Meinshausen, N.},
booktitle = {Advances in Neural Information Processing Systems 28 ({NIPS} 2015)},
pages = {1513--1521},
year = 2015
}
%publisher = {Curran Associates, Inc.},
%url = {http://papers.nips.cc/paper/5682-backshift-learning-causal-cyclic-graphs-from-unknown-shift-interventions.pdf}
%editor = {C. Cortes and N. D. Lawrence and D. D. Lee and M. Sugiyama and R. Garnett},

@InCollection{RiS99,
  author = {Richardson, T. and Spirtes, P.},
  title = {Automated discovery of linear feedback models},
  booktitle = 	 {Computation, Causation, and Discovery},
  publisher =    {MIT Press},
  year = 	 {1999},
  pages =        {253--304}
}
%  editor = {C.~Glymour and G.~F.~Cooper},

@inproceedings{HEJ14,
  author    = {Hyttinen, A. and Eberhardt, F. and J{\"{a}}rvisalo, M.},
  title     = {Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming},
  booktitle = {Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, ({UAI}-14)},
  pages     = {340--349},
  year      = {2014}
}

@article {HEH12,
    AUTHOR = {Hyttinen, A. and Eberhardt, F. and Hoyer, P.O.},
     TITLE = {Learning linear cyclic causal models with latent variables},
   JOURNAL = {Journal of Machine Learning Research},
    VOLUME = {13},
      YEAR = {2012},
     PAGES = {3387--3439}
}

@inproceedings{HEH10,
  author = {Hyttinen, A. and Eberhardt, F. and Hoyer, P.O.},
  title = {Causal discovery for linear cyclic models with latent variables},
  booktitle = {Proceedings of the Fifth European Workshop on Probabilistic Graphical Models ({PGM} 2010)},
  year = 2010,
  pages = {153-160}
}

@article{Mooij++_JMLR_2020,
  author = "Joris M. Mooij and Sara Magliacane and Tom Claassen",
  journal = "Journal of Machine Learning Research",
  title = "Joint Causal Inference from Multiple Contexts",
  volume = 21,
  number = 99,
  pages = {1-108},
  year = 2020,
}
@article{Mooij++_1611.10351v5,
  author = "Joris M. Mooij and Sara Magliacane and Tom Claassen",
  journal = "arXiv.org preprint",
  title = "Joint Causal Inference from Multiple Contexts",
  volume = "arXiv:1611.10351v5 [cs.LG]",
  year = 2020,
  month = Feb,
  url = "https://arxiv.org/abs/1611.10351v5",
  note = {Forthcoming in Journal of Machine Learning Research}
}

@inproceedings{ForreMooij_UAI_18,
  title     = {Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders},
  author    = {Patrick Forr{\'e} and Joris M. Mooij},
  booktitle = {Proceedings of the 34th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-18)},
  year      = 2018,
}

@article{GyorfiWalk2012,
  author = {L{\'a}szl{\'o} Gy{\"o}rfi and Harro Walk},
  title = {Strongly consistent nonparametric tests of conditional independence},
  journal = {Statistics \& Probability Letters},
  volume = 82,
  issue = 6,
  month = Jun,
  year = 2012,
  pages = {1145-1150},
}

@article{KalischBuehlmann2007,
	author = {Markus Kalisch and Peter B{\"u}hlmann},
	title = {Estimating High-Dimensional Directed Acyclic Graphs with the {PC}-Algorithm},
	journal = {Journal of Machine Learning Research},
	volume = 8,
	year = 2007,
	month = Mar,
	pages = {613--636}
}
@inproceedings{Meek1995,
author = {Christopher Meek},
year = 1995,
title = {Strong completeness and faithfulness in {B}ayesian networks},
booktitle = {Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence ({UAI}-95)},
pages = {411--419},
}

@inproceedings{ForreMooij_UAI_19,
  title     = {Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias},
  author    = {Patrick Forr{\'e} and Joris M. Mooij},
  booktitle = {Proceedings of the 35th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-19)},
  year      = 2019,
}

@article{Koster96,
  author =       {Jan T.A. Koster},
  title =        {{M}arkov properties of nonrecursive causal models},
  journal =      {Annals of Statistics},
  volume =       24,
  number =       5,
  pages =        {2148-2177},
  year =         1996
}

@article{Neal2000,
  title = {On Deducing Conditional Independence from $d$-Separation in Causal Graphs with Feedback},
  author = {R.M. Neal},
  journal = {Journal of Artificial Intelligence Research},
  year = 2000,
  volume = 12,
  pages = {87-91},
}

@inproceedings{PearlDechter96,
  author = {J. Pearl and R. Dechter},
  title = {Identifying Independence in Causal Graphs with Feedback},
  booktitle = {Proceedings of the 12th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-96)},
  year = 1996,
  pages = {420-426}
}

@article{Kos99,
  author = {J. T. A. Koster},
  title = {On the validity of the Markov interpretation of path diagrams of {G}aussian structural equations systems with correlated errors},
  journal = {Scandinavian Journal of Statistics},
  volume = 26,
  pages = {413-431},
  year = 1999
}

@article{SRMSG98,
  author = {P. Spirtes and T. Richardson and C. Meek and R. Scheines and C. Glymour},
  title = {Using path diagrams as a structural equation modelling tool},
  journal = {Sociological Methods \& Research},
  volume = 27,
  pages = {182-225},
  year = 1998
}

@inproceedings{Pearl1986,
  author = {J. Pearl},
  journal = {Uncertainty in Artificial Intelligence},
  title = {A Constraint Propagation Approach to Probabilistic Reasoning},
  booktitle = {Proceedings of the First Conference on Uncertainty in Artificial Intelligence ({UAI}-85)},
  pages = {357-370},
  year = 1986
}

@article{Wright1921,
  author = {S. Wright},
  journal = {Journal of Agricultural Research},
  pages = {557--585},
  title = {Correlation and Causation},
  volume = 20,
  year = 1921
}

@Book{Pearl2009x,
author =         {Judea Pearl},
title =          {Causality: Models, Reasoning and Inference},
year =   {2009},
publisher =      {Cambridge University Press},
address =        {}
}


@inproceedings{Roumpelaki++_UAIWS_16,
  title = {Marginal causal consistency in constraint-based causal learning},
  author = {Anna Roumpelaki and Giorgos Borboudakis and Sofia Triantafillou and Ioannis Tsamardinos},
  booktitle = {Proceedings of the UAI 2016 Workshop on Causation: Foundation to Application},
  pages = {39-47},
  url = {http://ceur-ws.org/Vol-1792/paper5.pdf},
  crossref = {UAI2016CFA},
}

@proceedings{UAI2016CFA,
  booktitle = {{UAI} 2016 Workshop on Causation: Foundation to Application},
  year = 2016,
  number = 1792,
  series = {{CEUR} Workshop Proceedings},
  issn = {1613-0073},
  url = {http://ceur-ws.org/Vol-1792},
  venue = {Jersey City, USA},
  eventdate = {2016-06-29},
  title = {Proceedings of the {UAI} 2016 Workshop on Causation: Foundation to Application}
}
%  address = {Aachen},
%  editor = {Frederick Eberhardt and Elias Bareinboim and Marloes Maathuis and Joris Mooij and Ricardo Silva},

@inproceedings{borboudakis2012tools,
  title={Tools and algorithms for causally interpreting directed edges in maximal ancestral graphs},
  author={Borboudakis, Giorgos and Triantafillou, Sofia and Tsamardinos, Ioannis},
  year=2012,
  booktitle={Proceedings of the Sixth European Workshop on Probabilistic Graphical Models ({PGM} 2012)},
  pages={35-42}
}

@article{ForreMooij_1710.08775,
  author = "Patrick Forr{\'e} and Joris M. Mooij",
  journal = "arXiv.org preprint",
  title = "Markov Properties for Graphical Models with Cycles and Latent Variables",
  volume = "arXiv:1710.08775 [math.ST]",
  year = 2017,
  month = Oct,
  url = "https://arxiv.org/abs/1710.08775",
}

@techreport{Spirtes94x,
author = {P. Spirtes},
year = 1994,
title = {Conditional Independence in Directed Cyclic Graphical Models for Feedback},
number = {CMU-PHIL-54},
institution = {Carnegie Mellon University}
}

@inproceedings{Spirtes95x,
  title = {Directed Cyclic Graphical Representations of Feedback Models},
  author = {P. Spirtes},
  booktitle = {Proceedings of the Eleventh Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-95)},
  pages = {499--506},
  year = 1995,
}
%  location = {Montreal, QU, USA},
%  month = 8, 
%  url = {https://dslpitt.org/papers/95/p499-spirtes.pdf}
%  editor = {Philippe Besnard and Steve Hanks},
%  publisher = {Morgan Kaufmann},
%  address = {San Francisco, CA, USA},

@article{Zhang2008_JMLR,
  author = {Zhang, Jiji},
  journal = {Journal of Machine Learning Research},
  volume =  {9},
  year = 2008,
  pages = {1437-1474},
  title = {Causal Reasoning with Ancestral Graphs}
}

@phdthesis{Zhang2006,
	author = {Jiji Zhang},
	month = Jul,
	year = 2006,
	title = {Causal Inference and Reasoning in Causally Insufficient Systems},
	school = {Carnegie Mellon University},
	url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.466.7206&rep=rep1&type=pdf}
}
