Publications - Kayvan Sadeghi

Kayvan Sadeghi


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Publications

  • Axiomatization of Interventional Probability Distributions. K. Sadeghi and T. Soo (2024), to appear in Biometrika

  • Relaxation and Construction of Localised Natural Causal Learning Algorithms, K. Teh, K. Sadeghi, and T. Soo (2024), to appear in UAI2024

  • Network Reliability Analysis and Complexity Quantification Using Bayesian Network and Dual Representation, D. Lee, J. E. Byun, K. Sadeghi , J. Song (2023), In proceedings of 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14)

  • Conditions and Assumptions for Constraint-based Causal Structure Learning, K. Sadeghi and T. Soo (2022), Journal of Machine Learning Research, 23, 1--34

  • On Finite Exchangeability and Conditional Independence, K. Sadeghi (2020), Electronic Journal of Statistics, 14 (2), 2773--2797

  • Hierarchical Models for Independence Structures of Networks, K. Sadeghi and A. Rinaldo (2020), Statistica Neerlandica, 74, 439--457

  • Markov Properties of Discrete Determinantal Point Processes (2019), K. Sadeghi and Alessandro Rinaldo, In Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019) (Proceedings of Machine Learning Research), 89, 1313--1321

  • On Exchangeability in Network Models (2019), S.L. Lauritzen, A. Rinaldo, and K. Sadeghi, Journal of Algebraic Statistics, 10 (1), 85--113

  • Unifying Markov Properties for Graphical Models (2018), S.L. Lauritzen and K. Sadeghi, Annals of Statistics, 46 (5), 2251--2278

  • Random Networks, Graphical Models, and Exchangeability (2018), S.L. Lauritzen, A. Rinaldo, and K. Sadeghi, Journal of the Royal Statistical Society Series B, 80 (3), 481--508

  • Faithfulness of Probability Distributions and Graphs (2017), K. Sadeghi, Journal of Machine Learning Research, 18 (148), 1--29

  • Total Positivity in Markov Structures (2017), S. Fallat, S.L. Lauritzen, K. Sadeghi, C. Uhler, N. Wermuth, and P. Zwiernik, Annals of Statistics, 45 (3), 1152--1184

  • On the Number of Non-zero Elements of Joint Degree Vectors (2017), E. Czabarka, J. Rauh, K. Sadeghi, T. Short, and G. Szekely, Electronic Journal of Combinatorics, 24 (1), P1.55

  • Pairwise Markov Properties for Regression Graphs (2016), K. Sadeghi and N. Wermuth, Stat, 5, 286--294

  • Marginalization and Conditioning for LWF Chain Graphs (2016), K. Sadeghi, Annals of Statistics, 44 (4), 1792--1816

  • Markov Properties for Mixed Graphs (2014), K. Sadeghi and S.L. Lauritzen, Bernoulli, 20 (2), 676--696

  • Beta Model for Hypergraphs (2014), D. Stasi, K. Sadeghi, A. Rinaldo, S. Petrovic, and S. Fienberg, In Proceedings of 21st International Conference on Computational Statistics, 593--600

  • Statistical Models for Degree Distributions of Networks (2014), K. Sadeghi and A. Rinaldo, NIPS workshop, Montreal, Canada

  • Stable Mixed Graphs (2013), K. Sadeghi, Bernoulli, 19 (5B), 2330--2358

  • Sequences of Regressions and their Independences (2012), N. Wermuth and K. Sadeghi, invited discussion paper in TEST, 21 (2), 215--252 and 274--279

  • Graphical Markov Models with Mixed Graphs in R (2012), K. Sadeghi and G.M. Marchetti, The R Journal, 4 (2), 65--73


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  • Markov Equivalences for Subclasses of Loopless Mixed Graphs (2011), , K. Sadeghi, arXiv:1110.4539


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  • Graphical Representation of Independence Structures (2012), K. Sadeghi, DPhil thesis, University of Oxford

  • Graph Theoretical Proofs for Separation Criteria (2008), K. Sadeghi, MSc Thesis, Chalmers University of Technology