Search Results - Mooij, Joris M.

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  1. 1
    MAGMA: generalized gene-set analysis of GWAS data

    MAGMA: generalized gene-set analysis of GWAS data by de Leeuw, Christiaan A, Mooij, Joris M, Heskes, Tom, Posthuma, Danielle

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  2. 2
    Sufficient Conditions for Convergence of the Sum-Product Algorithm

    Sufficient Conditions for Convergence of the Sum-Product Algorithm by Mooij, J.M., Kappen, H.J.

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  3. 3
    Methods for causal inference from gene perturbation experiments and validation

    Methods for causal inference from gene perturbation experiments and validation by Meinshausen, Nicolai, Hauser, Alain, Mooij, Joris M., Peters, Jonas, Versteeg, Philip, Bühlmann, Peter

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  4. 4
    Causality and independence in perfectly adapted dynamical systems

    Causality and independence in perfectly adapted dynamical systems by Blom, Tineke, Mooij, Joris M.

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  5. 5
    MAGMA: Generalized Gene-Set Analysis of GWAS Data: e1004219

    MAGMA: Generalized Gene-Set Analysis of GWAS Data: e1004219 by Leeuw, Christiaan Ade, Mooij, Joris M, Heskes, Tom, Posthuma, Danielle

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  6. 6
    Dynamic Structural Causal Models

    Dynamic Structural Causal Models by Boeken, Philip, Mooij, Joris M

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  7. 7
    Boosting Local Causal Discovery in High-Dimensional Expression Data

    Boosting Local Causal Discovery in High-Dimensional Expression Data by Versteeg, Philip, Mooij, Joris M

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  8. 8
    Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles

    Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles by Mooij, Joris M, Claassen, Tom

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  9. 9
    Establishing Markov Equivalence in Cyclic Directed Graphs

    Establishing Markov Equivalence in Cyclic Directed Graphs by Claassen, Tom, Mooij, Joris M

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  10. 10
    Nonparametric Bayesian networks are typically faithful in the total variation metric

    Nonparametric Bayesian networks are typically faithful in the total variation metric by Boeken, Philip, ré, Patrick, Mooij, Joris M

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  11. 11
    Causality and independence in perfectly adapted dynamical systems

    Causality and independence in perfectly adapted dynamical systems by Blom, Tineke, Mooij, Joris M

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  12. 12
    Modeling Latent Selection with Structural Causal Models

    Modeling Latent Selection with Structural Causal Models by Chen, Leihao, Zoeter, Onno, Mooij, Joris M

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  13. 13
    Robustness of Model Predictions under Extension

    Robustness of Model Predictions under Extension by Blom, Tineke, Mooij, Joris M

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  14. 14
    Evaluating and Correcting Performative Effects of Decision Support Systems via Causal Domain Shift

    Evaluating and Correcting Performative Effects of Decision Support Systems via Causal Domain Shift by Boeken, Philip, Zoeter, Onno, Mooij, Joris M

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  15. 15
    Foundations of Structural Causal Models with Cycles and Latent Variables

    Foundations of Structural Causal Models with Cycles and Latent Variables by Bongers, Stephan, ré, Patrick, Peters, Jonas, Mooij, Joris M

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  16. 16
    Causal Modeling of Dynamical Systems

    Causal Modeling of Dynamical Systems by Bongers, Stephan, Blom, Tineke, Mooij, Joris M

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  17. 17
    Local Constraint-Based Causal Discovery under Selection Bias

    Local Constraint-Based Causal Discovery under Selection Bias by Versteeg, Philip, Zhang, Cheng, Mooij, Joris M

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  18. 18
    A Bayesian Nonparametric Conditional Two-sample Test with an Application to Local Causal Discovery

    A Bayesian Nonparametric Conditional Two-sample Test with an Application to Local Causal Discovery by Boeken, Philip A, Mooij, Joris M

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  19. 19
    A Weaker Faithfulness Assumption based on Triple Interactions

    A Weaker Faithfulness Assumption based on Triple Interactions by Marx, Alexander, Gretton, Arthur, Mooij, Joris M

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  20. 20
    Combining Interventional and Observational Data Using Causal Reductions

    Combining Interventional and Observational Data Using Causal Reductions by Ilse, Maximilian, ré, Patrick, Welling, Max, Mooij, Joris M

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