BibTeX entries
Published journal articles and conference proceedings
@inproceedings{Boeken++_UAI_23,
title = {Correcting for selection bias and missing response in regression using privileged information},
author = {Philip Boeken and Noud de Kroon and Mathijs de Jong and Joris M. Mooij and Onno Zoeter},
booktitle = {Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence ({UAI}-23)},
year = {2023},
editor = {Evans, Robin J. and Shpitser, Ilya},
volume = {216},
pages = {195--205},
series = {Proceedings of Machine Learning Research},
month = 08,
publisher = {PMLR},
url = {https://proceedings.mlr.press/v216/boeken23a.html},
}
@inproceedings{ClaassenMooij_UAI_23,
title = {Establishing Markov equivalence in cyclic directed graphs},
author = {Tom Claassen and Joris M. Mooij},
booktitle = {Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence ({UAI}-23)},
year = {2023},
editor = {Evans, Robin J. and Shpitser, Ilya},
volume = {216},
pages = {433--442},
series = {Proceedings of Machine Learning Research},
month = 08,
publisher = {PMLR},
url = {https://proceedings.mlr.press/v216/boeken23a.html},
}
@article{Claassen_Mooij_2309.03092,
title = {Establishing Markov equivalence in cyclic directed graphs},
author = {Tom Claassen and Joris M. Mooij},
journal = {arXiv.org preprint},
volume = {arXiv:2309.03092 [cs.AI]},
url = {https://arxiv.org/abs/2309.03092},
month = 9,
year = 2023,
}
@article{BlomMooij_JCI_23,
author = {Tineke Blom and Joris M. Mooij},
journal = {Journal of Causal Inference},
title = {Causality and Independence in Perfectly Adapted Dynamical Systems},
volume = 11,
issue = 1,
pages = {20210005},
year = 2023,
url = {https://www.degruyter.com/document/doi/10.1515/jci-2021-0005/html},
}
@inproceedings{BlomMooij_UAI_22,
title = {Robustness of Model Predictions under Extension},
author = {Blom, Tineke and Mooij, Joris M.},
booktitle = {Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence ({UAI}-22)},
pages = {213--222},
year = {2022},
editor = {Cussens, James and Zhang, Kun},
volume = {180},
series = {Proceedings of Machine Learning Research},
month = 08,
publisher = {PMLR},
url = {https://proceedings.mlr.press/v180/blom22a.html},
}
@inproceedings{DeKroonBelgraveMooij_CLEAR_22,
title = {Causal Bandits without Prior Knowledge using Separating Sets},
author = {De Kroon, Arnoud A. W. M. and Belgrave, Danielle and Mooij, Joris M.},
booktitle = {Proceedings of the First Conference on Causal Learning and Reasoning ({CLEAR}-22)},
pages = {407--427},
year = {2022},
editor = {Sch{\"o}lkopf, Bernhard and Uhler, Caroline and Zhang, Kun},
volume = {177},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
url = {https://proceedings.mlr.press/v177/kroon22a.html},
}
@inproceedings{VersteegZhangMooij_CLEAR_22,
title = {Local Constraint-Based Causal Discovery under Selection Bias},
author = {Versteeg, Philip and Zhang, Cheng and Mooij, Joris M.},
booktitle = {Proceedings of the First Conference on Causal Learning and Reasoning ({CLEAR}-22)},
pages = {840--860},
year = {2022},
editor = {Sch{\"o}lkopf, Bernhard and Uhler, Caroline and Zhang, Kun},
volume = {177},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
url = {https://proceedings.mlr.press/v177/versteeg22a.html},
}
@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{BlomVanDiepenMooij_JMLR_21,
author = {Tineke Blom and Mirthe M. van Diepen and Joris M. Mooij},
title = {Conditional Independences and Causal Relations implied by Sets of Equations},
journal = {Journal of Machine Learning Research},
year = {2021},
volume = {22},
number = {178},
pages = {1-62},
url = {http://jmlr.org/papers/v22/20-863.html}
}
@inproceedings{BoekenMooij_UAI_21,
title = {A {B}ayesian Nonparametric Conditional Two-sample Test with an Application to Local Causal Discovery},
author = {Boeken, Philip A. and Mooij, Joris M.},
booktitle = {Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence ({UAI}-21)},
pages = {1565--1575},
year = 2021,
editor = {de Campos, Cassio and Maathuis, Marloes H.},
volume = 161,
series = {Proceedings of Machine Learning Research},
month = 7,
publisher = {PMLR},
url = {https://proceedings.mlr.press/v161/boeken21a.html},
}
@inproceedings{MarxGrettonMooij_UAI_21,
title = {A Weaker Faithfulness Assumption based on Triple Interactions},
author = {Alexander Marx and Arthur Gretton and Joris M. Mooij},
booktitle = {Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence ({UAI}-21)},
pages = {451--460},
year = 2021,
editor = {de Campos, Cassio and Maathuis, Marloes H.},
volume = 161,
series = {Proceedings of Machine Learning Research},
month = 7,
publisher = {PMLR},
url = {https://proceedings.mlr.press/v161/marx21a.html},
}
@inproceedings{MooijClaassen_UAI_20,
title = {Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles},
author = {Joris M. Mooij and Tom Claassen},
booktitle = {Proceedings of the 36th Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-20)},
editor = {Jonas Peters and David Sontag},
publisher = {PMLR},
volume = 124,
pages = {1159--1168},
year = 2020,
month = 8,
url = {http://proceedings.mlr.press/v124/m-mooij20a/m-mooij20a-supp.pdf}
}
@article{Mooij++_JMLR_20,
author = {Joris M. Mooij and Sara Magliacane and Tom Claassen},
title = {Joint Causal Inference from Multiple Contexts},
journal = {Journal of Machine Learning Research},
year = {2020},
volume = {21},
number = {99},
pages = {1-108},
url = {http://jmlr.org/papers/v21/17-123.html}
}
@inproceedings{VersteegMooij_BIBM_19,
author = {Philip Versteeg and Joris M. Mooij},
booktitle = {2019 IEEE International Conference on Bioinformatics and Biomedicine ({BIBM})},
title = {Boosting Local Causal Discovery in High-Dimensional Expression Data},
year = {2019},
pages = {2599-2604},
doi = {10.1109/BIBM47256.2019.8983232},
url = {https://doi.ieeecomputersociety.org/10.1109/BIBM47256.2019.8983232},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
month = 11
}
@inproceedings{BlomBongersMooij_UAI_19,
title = {Beyond Structural Causal Models: Causal Constraints Models},
author = {Tineke Blom and Stephan Bongers and Joris M. Mooij},
pages = {585-594},
url = {https://proceedings.mlr.press/v115/blom20a.html},
booktitle = {Proceedings of the 35th Uncertainty in Artificial Intelligence Conference ({UAI}-19)},
editor = {Adams, Ryan P. and Gogate, Vibhav},
year = 2020,
publisher = {PMLR},
series = {Proceedings of Machine Learning Research},
month = 7,
volume = 115,
}
@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},
pages = {71--80},
url = {https://proceedings.mlr.press/v115/forre20a.html},
booktitle = {Proceedings of the 35th Uncertainty in Artificial Intelligence Conference ({UAI}-19)},
editor = {Adams, Ryan P. and Gogate, Vibhav},
year = 2020,
publisher = {PMLR},
series = {Proceedings of Machine Learning Research},
month = 7,
volume = 115,
}
@incollection{Magliacane++_NeurIPS_18,
title = {Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions},
author = {Magliacane, Sara and van Ommen, Thijs and Claassen, Tom and Bongers, Stephan and Versteeg, Philip and Mooij, Joris M},
booktitle = {Advances in Neural Information Processing Systems 31 ({N}eur{IPS}2018)},
editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
pages = {10869--10879},
year = {2018},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/8282-domain-adaptation-by-using-causal-inference-to-predict-invariant-conditional-distributions.pdf}
}
@inproceedings{Blom++_UAI_18,
title = {An Upper Bound for Random Measurement Error in Causal Discovery},
author = {Tineke Blom and Anna Klimovskaia and Sara Magliacane and Joris M. Mooij},
booktitle = {Proceedings of the 34th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-18)},
pages = {570-579},
year = 2018,
}
@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)},
pages = {269-278},
year = 2018,
}
@inproceedings{Rubenstein++_UAI_18,
title = {From Deterministic {ODE}s to Dynamic Structural Causal Models},
author = {Paul K. Rubenstein and Stephan Bongers and Bernhard Sch{\"o}lkopf and Joris M. Mooij},
booktitle = {Proceedings of the 34th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-18)},
pages = {114-123},
year = 2018,
}
@inproceedings{VanOmmenMooij_UAI_17,
title = {Algebraic Equivalence of Linear Structural Equation Models},
author = {Thijs van Ommen and Joris M. Mooij},
booktitle = {Proceedings of the 33rd Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-17)},
year = 2017,
}
@incollection{Louizos++_NIPS_17,
author = {Christos Louizos and Uri Shalit and Joris M. Mooij and David Sontag and Richard Zemel and Max Welling},
title = {Causal Effect Inference with Deep Latent-Variable Models},
booktitle = {Advances in Neural Information Processing Systems 30},
editor = {I. Guyon and U. V. Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett},
pages = {6449--6459},
year = 2017,
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/7223-causal-effect-inference-with-deep-latent-variable-models.pdf}
}
@inproceedings{Rubenstein++_UAI_17,
title = {Causal Consistency of Structural Equation Models},
author = {Paul K. Rubenstein and Sebastian Weichwald and Stephan Bongers and Joris M. Mooij and Dominik Janzing and Moritz Grosse-Wentrup and Bernhard Sch{\"o}lkopf},
booktitle = {Proceedings of the 33rd Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-17)},
year = 2017,
}
@incollection{MagliacaneClaassenMooij_NIPS_16,
title = {Ancestral Causal Inference},
author = {Magliacane, Sara and Claassen, Tom and Mooij, Joris M},
booktitle = {Advances in Neural Information Processing Systems 29},
editor = {D. D. Lee and M. Sugiyama and U. V. Luxburg and I. Guyon and R. Garnett},
pages = {4466--4474},
year = {2016},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/6266-ancestral-causal-inference.pdf}
}
@article{Meinshausen++_PNAS_16,
author = {Nicolai Meinshausen and Alain Hauser and Joris M. Mooij and Jonas Peters and Philip Versteeg and Peter B{\"u}hlmann},
title = {Methods for causal inference from gene perturbation experiments and validation},
journal = {Proceedings of the National Academy of Sciences of the {U}nited {S}tates of {A}merica},
year = {2016},
volume = {113},
number = {27},
pages = {7361-7368},
url = {http://www.pnas.org/content/113/27/7361.abstract?sid=0ce8e45d-586d-4272-b50e-5a326f9495ef}
}
@article{Mooij++_JMLR_16,
author = {Joris M. Mooij and Jonas Peters and Dominik Janzing and Jakob Zscheischler and Bernhard Sch{\"o}lkopf},
title = {Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks},
journal = {Journal of Machine Learning Research},
year = {2016},
volume = {17},
number = {32},
pages = {1-102},
url = {http://jmlr.org/papers/v17/14-518.html}
}
@inproceedings{MooijCremers_UAI2015CI,
title = {An Empirical Study of one of the Simplest Causal Prediction Algorithms},
author = {Joris M. Mooij and Jerome Cremers},
pages = {30--39},
url = {http://ceur-ws.org/Vol-1504/uai2015aci_paper2.pdf},
crossref = {UAI2015CI},
}
@proceedings{UAI2015CI,
booktitle = {{UAI} 2015 Workshop on Advances in Causal Inference},
year = 2015,
editor = {Ricardo Silva and Ilya Shpitser and Robin J. Evans and Jonas Peters and Tom Claassen},
number = 1504,
series = {{CEUR} Workshop Proceedings},
address = {Aachen},
issn = {1613-0073},
url = {http://ceur-ws.org/Vol-1504},
venue = {Amsterdam, The Netherlands},
eventdate = {2016-07-16},
title = {Proceedings of the {UAI} 2015 Workshop on Advances in Causal Inference},
}
@article{DeLeeuwMooijHeskesPosthuma_15,
author = {de Leeuw, Christiaan A. AND Mooij, Joris M. AND Heskes, Tom AND Posthuma, Danielle},
journal = {PLoS Computational Biology},
publisher = {Public Library of Science},
title = {{MAGMA}: Generalized Gene-Set Analysis of {GWAS} Data},
year = {2015},
month = {04},
volume = {11},
url = {http://dx.doi.org/10.1371%2Fjournal.pcbi.1004219},
pages = {e1004219},
number = {4},
doi = {10.1371/journal.pcbi.1004219}
}
@inproceedings{CorniaMooij_UAI2014CI,
title = {Type-{II} Errors of Independence Tests Can Lead to Arbitrarily Large Errors in Estimated Causal Effects: An Illustrative Example},
author = {Nicholas Cornia and Joris M. Mooij},
pages = {35--42},
url = {http://ceur-ws.org/Vol-1274/uai2014ci_paper7.pdf},
crossref = {UAI2014CI},
}
@proceedings{UAI2014CI,
booktitle = {{UAI} 2014 Workshop Causal Inference: Learning and Prediction},
year = 2014,
editor = {Joris M. Mooij and Dominik Janzing and Jonas Peters and Tom Claassen and Antti Hyttinen},
number = 1274,
series = {{CEUR} Workshop Proceedings},
address = {Aachen},
issn = {1613-0073},
url = {http://ceur-ws.org/Vol-1274},
venue = {Quebec City, Quebec, Canada},
eventdate = {2014-07-27},
title = {Proceedings of the {UAI} 2014 Workshop Causal Inference: Learning and Prediction},
}
@article{PetersMooijJanzingSchoelkopf_JMLR_14,
author = {Jonas Peters and Joris M. Mooij and Dominik Janzing and Bernhard Sch{\"o}lkopf},
title = {Causal Discovery with Continuous Additive Noise Models},
journal = {Journal of Machine Learning Research},
year = {2014},
volume = {15},
pages = {2009-2053},
url = {http://jmlr.org/papers/v15/peters14a.html}
}
@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{MooijJanzingSchoelkopf_UAI_13,
title = {From Ordinary Differential Equations to Structural Causal Models: the deterministic case},
author = {Joris M. Mooij and Dominik Janzing and Bernhard Sch{\"o}lkopf},
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 = {440--448},
url = {http://auai.org/uai2013/prints/papers/24.pdf}
}
@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,
location = {Corvallis, Oregon},
publisher = {AUAI Press},
editor = {Ann Nicholson and Padhraic Smyth},
pages = {172--181},
url = {http://auai.org/uai2013/prints/papers/121.pdf}
}
@inproceedings{Schoelkopf_et_al_ICML_12,
title = {On causal and anticausal learning},
author = {Bernhard Sch{\"o}lkopf and Dominik Janzing and Jonas Peters and Eleni Sgouritsa and Kun Zhang and Joris M. Mooij},
url = {http://icml.cc/2012/papers/625.pdf},
booktitle = {Proceedings of the 29th {I}nternational {C}onference on {M}achine {L}earning ({ICML} 2012)},
year = 2012,
series = {ICML '12},
editor = {John Langford and Joelle Pineau},
location = {Edinburgh, Scotland, GB},
isbn = {978-1-4503-1285-1},
month = {July},
publisher = {Omnipress},
address = {New York, NY, USA},
pages= {1255--1262}
}
@article{Janzing_et_al_AI_12,
title = {Information-geometric approach to inferring causal directions},
author = {Dominik Janzing and Joris M. Mooij and Kun Zhang and Jan Lemeire and Jacob Zscheischler and Povilas Daniu{\v s}is and Bastian Steudel and Bernhard Sch{\"o}lkopf},
journal = {Artificial Intelligence},
volume = {182-183},
pages = {1-31},
year = 2012,
issn = {0004-3702},
doi = {10.1016/j.artint.2012.01.002},
url = {http://www.sciencedirect.com/science/article/pii/S0004370212000045}
}
@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{Stegle_et_al_NIPS_11,
author = {Oliver Stegle and Christoph Lippert and Joris M. Mooij and Neil D. Lawrence and Karsten Borgwardt},
title = {Efficient inference in matrix-variate Gaussian models with iid observation noise},
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 = {630--638},
year = {2011},
url = {http://books.nips.cc/papers/files/nips24/NIPS2011_0443.pdf}
}
@inproceedings{Quinn_et_al_ESANN_11,
title = {Learning of causal relations},
author = {John Quinn and Joris M. Mooij and Tom Heskes and Michael Biehl},
booktitle = {Proceedings of the 19th European Symposium on Artificial Neural Networks (ESANN 2011)},
year = 2011,
url = {http://www.dice.ucl.ac.be/esann/proceedings/papers.php?ann=2011#9}
}
@inproceedings{Peters_et_al_UAI_11,
title = {Identifiability of Causal Graphs using Functional Models},
author = {Jonas Peters and Joris M. Mooij and Dominik Janzing and Bernhard Sch{\"o}lkopf},
booktitle = {Proceedings of the 27th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-11)},
year = 2011,
location = {Corvallis, Oregon},
publisher = {AUAI Press},
editor = {Fabio G. Cozman and Avi Pfeffer},
pages = {589--598},
url = {http://uai.sis.pitt.edu/papers/11/p589-peters.pdf}
}
@article{Martens_et_al_NeurComp_11,
author = {Suzanne M. M. Martens and Joris M. Mooij and N. J. Hill and Jason Farquhar and Bernhard Sch{\"o}lkopf},
title = {A Graphical Model Framework for Decoding in the Visual {ERP}-Based {BCI} Speller},
journal = {Neural Computation},
year = 2011,
month = Jan,
volume = 23,
number = 1,
pages = {160-182},
url = {http://www.mitpressjournals.org/doi/abs/10.1162/NECO_a_00066}
}
@inproceedings{Mooij_et_al_NIPS_10,
author = {Joris M. Mooij and Oliver Stegle and Dominik Janzing and Kun Zhang and Bernhard Sch{\"o}lkopf},
title = {Probabilistic latent variable models for distinguishing between cause and effect},
booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems 23 ({NIPS}*2010)},
editor = {J. Lafferty and C. K. I. Williams and J. Shawe-Taylor and R.S. Zemel and A. Culotta},
pages = {1687--1695},
year = {2010},
url = {http://books.nips.cc/papers/files/nips23/NIPS2010_1270.pdf}
}
@article{Mooij_JMLR_MLOSS_10,
author = {Joris M. Mooij},
title = {lib{DAI}: A Free and Open Source {CEtAl} Library for Discrete Approximate Inference in Graphical Models},
journal = {Journal of Machine Learning Research},
year = 2010,
month = Aug,
volume = 11,
pages = {2169-2173},
url = {http://www.jmlr.org/papers/volume11/mooij10a/mooij10a.pdf}
}
@inproceedings{Daniusis_et_al_UAI_10,
title = {Inferring deterministic causal relations},
author = {Povilas Daniu{\v s}is and Dominik Janzing and Joris M. Mooij and Jakob Zscheischler and Bastian Steudel and Kun Zhang and Bernhard Sch{\"o}lkopf},
booktitle = {Proceedings of the 26th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-10)},
year = 2010,
location = {},
publisher = {},
editor = {},
pages = {},
url = {http://event.cwi.nl/uai2010/papers/UAI2010_0121.pdf}
}
@article{CampsVallsMooijSchoelkopf_10,
title = {Remote Sensing Feature Selection by Kernel Dependence Measures},
author = {Gustavo Camps-Valls and Joris M. Mooij and Bernhard Sch\"{o}lkopf},
journal = {{IEEE} Geoscience and Remote Sensing Letters},
volume = 7,
number = 3,
month = Jul,
year = 2010,
pages = {587-591}
}
@inproceedings{MooijJanzing_JMLR_10,
title = {Distinguishing between cause and effect},
author = {Joris M. Mooij and Dominik Janzing},
booktitle = {Journal of Machine Learning Research Workshop and Conference Proceedings},
volume = {6},
year = 2010,
pages = {147-156}
}
@inproceedings{JanzingPetersMooijSchoelkopf_UAI_09,
title = {Identifying confounders using additive noise models},
author = {Dominik Janzing and Jonas Peters and Joris M. Mooij and Bernhard Sch\"{o}lkopf},
booktitle = {Proceedings of the 25th Annual Conference on {U}ncertainty in {A}rtificial {I}ntelligence ({UAI}-09)},
year = 2009,
location = {},
publisher = {},
editor = {},
pages = {},
url = {http://www.cs.mcgill.ca/~uai2009/papers/UAI2009_0118_d5787036a879b5fb06ab513f53eb06a7.pdf}
}
@incollection{MooijKappen_NIPS_08,
title = {Bounds on marginal probability distributions},
author = {Joris M. Mooij and Hilbert J. Kappen},
booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems 21 ({NIPS}*2008)},
editor = {D. Koller and D. Schuurmans and Y. Bengio and L. Bottou},
pages = {1105--1112},
year = {2009}
}
@article{MooijKappen_IEEETIT_07,
author = "Joris M. Mooij and Hilbert J. Kappen",
journal = "IEEE Transactions on Information Theory",
title = "Sufficient Conditions for Convergence of the Sum-Product Algorithm",
volume = 53,
number = 12,
month = Dec,
year = 2007,
pages = "4422-4437",
doi = "10.1109/TIT.2007.909166"
}
@article{GomezMooijKappen_JMLR_07,
author = "Vicen\c{c} G{\'o}mez and Joris M. Mooij and Hilbert J. Kappen",
title = "Truncating the Loop Series Expansion for Belief Propagation",
journal = "Journal of Machine Learning Research",
year = 2007,
volume = 8,
month = Sep,
pages = "1987-2016",
url = "http://www.jmlr.org/papers/volume8/gomez07a/gomez07a.pdf",
}
@article{MooijKappen_JMLR_07,
author = "Joris M. Mooij and Hilbert J. Kappen",
title = "Loop Corrections for Approximate Inference on Factor Graphs",
journal = "Journal of Machine Learning Research",
year = 2007,
month = May,
volume = 8,
pages = "1113-1143",
url = "http://www.jmlr.org/papers/volume8/mooij07a/mooij07a.pdf"
}
@inproceedings{WemmenhoveMooijWiegerinckLeisinkKappenNeijt_AIME_07,
author = "Bastian Wemmenhove and Joris M. Mooij and Wim Wiegerinck and Martijn Leisink and Hilbert J. Kappen and Jan P. Neijt",
title = "Inference in the {P}romedas medical expert system",
booktitle = "Proceedings of the 11th Conference on Artificial Intelligence in Medicine (AIME 2007)",
year = 2007,
editors = "R. Bellazzi and A. Abu-Hanna and J. Hunter",
series = "Lecture Notes in Computer Science",
volume = 4594,
isbn = "978-3-540-73598-4",
publisher = "Springer",
pages = {456--460},
doi = {10.1007/978-3-540-73599-1_61}
}
@inproceedings{MooijWemmenhoveKappenRizzo_AISTATS_07,
author = "Joris M. Mooij and Bastian Wemmenhove and Hilbert J. Kappen and Tommaso Rizzo",
title = "Loop Corrected Belief Propagation",
booktitle = "Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07)",
editors = "Marina Meila and Xiaotong Shen",
url = "http://www.stat.umn.edu/~aistat/proceedings/start.htm",
year = 2007,
volume = 11
}
@inproceedings{MooijKappen_UAI_05,
author = "Joris M. Mooij and Hilbert J. Kappen",
title = "Sufficient conditions for convergence of Loopy Belief Propagation",
booktitle = "Proceedings of the 21st Annual Conference on Uncertainty in Artificial Intelligence (UAI-05)",
year = 2005,
pages = {396-403},
publisher = "AUAI Press",
address = "Corvallis, Oregon",
editor = "F. Bacchus and T. Jaakkola"
}
@article{MooijKappen_JSTAT_05,
author = "Joris M. Mooij and Hilbert J. Kappen",
title = "On the properties of the {B}ethe approximation and Loopy Belief Propagation on binary networks",
journal = "Journal of Statistical Mechanics: Theory and Experiment",
volume = 2005,
number = 11,
pages = "P11012",
year = 2005,
url = "http://stacks.iop.org/1742-5468/2005/P11012"
}
@inproceedings{MooijKappen_NIPS_04,
author = "Joris M. Mooij and Hilbert J. Kappen",
title = "Validity estimates for Loopy Belief Propagation on binary real-world networks",
booktitle = "Advances in Neural Information Processing Systems 17 (NIPS*2004)",
year = 2005,
editor = "L. K. Saul and Y. Weiss and L. Bottou",
publisher = "MIT Press",
address = "Cambridge, MA",
pages = "945--952"
}
@article{TolboomDamTerMeulenMooijMaassen_ApplOpts_04,
author = "Ren{\'e} Tolboom and Nico Dam and Hans ter Meulen and Joris M. Mooij and Hans Maassen",
journal = "Applied Optics",
title = "Quantitative Imaging through a Spectrograph. 1. {P}rinciples and Theory",
volume = 43,
year = 2004,
pages = "5669-5681",
url = "http://www.opticsinfobase.org/abstract.cfm?URI=ao-43-30-5669"
}
Miscellaneous
@article{Mooij_NAW_23,
author = "Joris M. Mooij",
title = "Causality: from data to science",
year = 2023,
volume = 24,
issue = 2,
month = 6,
pages = {76-87},
journal = {Nieuw Archief voor Wiskunde},
}
@misc{Mooij_Inaugural_Lecture_22,
author = "Joris M. Mooij",
title = "Causality: from data to science",
url = "https://hdl.handle.net/11245.1/c6ad8128-00aa-4de4-8e51-f099fec54262",
howpublished = "\url{https://hdl.handle.net/11245.1/c6ad8128-00aa-4de4-8e51-f099fec54262}",
year = 2022,
note = "Inaugural speech, delivered on October 13, 2022"
}
@inproceedings{JanzingLauritzenSchoelkopf_Dagstuhl_09,
author = {Dominik Janzing and Steffen Lauritzen and Bernhard Sch{\"o}lkopf},
title = {09401 Abstracts Collection -- Machine learning approaches to statistical dependences and causality},
booktitle = {Machine learning approaches to statistical dependences and causality},
year = {2010},
editor = {Dominik Janzing and Steffen Lauritzen and Bernhard Sch{\"o}lkopf},
number = {09401},
series = {Dagstuhl Seminar Proceedings},
ISSN = {1862-4405},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2010/2363},
annote = {Keywords: Machine learning, statistical dependences, causality}
}
@misc{MooijJanzingSchoelkopf_CWR_08,
author = "Joris M. Mooij and Dominik Janzing and Bernhard Schoelkopf",
title = "Distinguishing between cause and effect",
year = "2008",
month = "10",
url = "http://www.kyb.tuebingen.mpg.de/bs/people/jorism/causality-data/",
institution = "Causality workbench repository"
}
@misc{Mooij_libDAI,
author = "Joris M. Mooij",
title = "{libDAI}: A free/open source {C}++ library for {D}iscrete {A}pproximate {I}nference",
year = 2006,
howpublished = "\url{http://www.libdai.org/}"
}
@phdthesis{Mooij_PhD_08,
author = "Joris M. Mooij",
title = "Understanding and Improving Belief Propagation",
school = "Radboud University Nijmegen",
year = 2008,
month = May,
url = "http://webdoc.ubn.ru.nl/mono/m/mooij_j/undeanimb.pdf"
}
Preprints and technical reports
@article{BoekenForreMooij_2410.16004,
title = {Nonparametric {B}ayesian networks are typically faithful in the total variation metric},
author = {Philip Boeken and Patrick Forr\'e and Joris M. Mooij},
journal = {arXiv.org preprint},
volume = {arXiv:2410.16004 [math.ST]},
url = {https://arxiv.org/abs/2410.16004},
month = 10,
year = 2024,
@article{Pandeva++_2409.19991,
title = {Robust Multi-view Co-expression Network Inference},
author = {Teodora Pandeva and Martijs Jonker and Leendert Hamoen and Joris M. Mooij and Patrick Forré},
journal = {arXiv.org preprint},
volume = {arXiv:2409.19991 [stat.ML]},
url = {https://arxiv.org/abs/2409.19991},
month = 9,
year = 2024,
}
@article{BoekenZoeterMooij_2403.00886,
title = {Evaluating and Correcting Performative Effects of Decision Support Systems via Causal Domain Shift},
author = {Philip Boeken and Onno Zoeter and Joris M. Mooij},
journal = {arXiv.org preprint},
volume = {arXiv:2403.00886 [cs.LG]},
url = {https://arxiv.org/abs/2403.00886},
month = 3,
year = 2024,
}
@article{ChenZoeterMooij_2401.06925,
title = {Modeling Latent Selection with Structural Causal Models},
author = {Leihao Chen and Onno Zoeter and Joris M. Mooij},
journal = {arXiv.org preprint},
volume = {arXiv:2401.06925 [cs.AI]},
url = {https://arxiv.org/abs/2401.06925},
month = 1,
year = 2024,
}
@article{Ilse++_2103.04786v3,
title = {Combining Interventional and Observational Data using Causal Reductions},
author = {Maximilian Ilse and Patrick Forr{\'e} and Max Welling and Joris M. Mooij},
journal = {arXiv.org preprint},
volume = {arXiv:2103.04786v3 [stat.ML]},
url = {https://arxiv.org/abs/2103.04786v3},
month = 2,
year = 2023,
}
@article{Ilse++_2103.04786,
title = {Efficient Causal Inference from Combined Observational and Interventional Data through Causal Reductions},
author = {Maximilian Ilse and Patrick Forr{\'e} and Max Welling and Joris M. Mooij},
journal = {arXiv.org preprint},
volume = {arXiv:2103.04786 [stat.ML]},
url = {https://arxiv.org/abs/2103.04786},
month = 3,
year = 2021,
}
@article{BongersBlomMooij_1803.08784v4,
author = "Stephan Bongers and Tineke Blom and Joris M. Mooij",
journal = "arXiv.org preprint",
title = "Causal Modeling of Dynamical Systems",
volume = "arXiv:1803.08784v4 [cs.AI]",
year = 2022,
month = Mar,
url = "https://arxiv.org/abs/1803.08784v4",
}
@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",
}
@article{ClaassenMooijHeskes_1411.1557,
author = "Tom Claassen and Joris M. Mooij and Tom Heskes",
journal = "ar{X}iv.org preprint",
title = "Proof Supplement - Learning Sparse Causal Models is not {NP}-hard ({UAI2013})",
volume = "ar{X}iv:1411.1577 [stat.{ML}]",
year = 2014,
month = Nov,
url = "http://arxiv.org/abs/1411.1557",
note = "Supplement to ``{L}earning Sparse Causal Models is not {NP}-hard'' ({UAI2013})"
}
@article{MooijKappen_0801.3797,
author = "Joris M. Mooij and Hilbert J. Kappen",
journal = "arXiv.org preprint",
title = "Novel Bounds on Marginal Probabilities",
volume = "arXiv:0801.3797 [math.PR]",
year = 2008,
month = Jan,
url = "http://arxiv.org/abs/0801.3797",
note = "Submitted to Journal of Machine Learning Research"
}
@article{MooijKappen_cs_0612030,
author = "Joris M. Mooij and Hilbert J. Kappen",
journal = "arXiv.org preprint",
title = "Loop corrections for approximate inference",
volume = "arXiv:cs/0612030v1 [cs.AI]",
year = 2006,
month = Dec,
url = "http://arxiv.org/abs/cs/0612030v1"
}
@article{MooijKappen_cond-mat_0408378v2,
author = "Joris M. Mooij and Hilbert J. Kappen",
journal = "arXiv.org preprint",
title = "Spin-glass phase transitions on real-world graphs",
volume = "arXiv:cond-mat/0408378v2 [cond-mat.stat-mech]",
year = 2004,
month = Sep,
url = "http://arxiv.org/abs/cond-mat/0408378v2"
}
Lecture notes
@misc{BoutenMooij_04,
author = "Luc Bouten and Joris M. Mooij",
title = "Toepassingen Groepentheorie",
year = 2004,
note = "Lecture notes",
howpublished = "Radboud University Nijmegen"
}
