Graphical Markov Models with Mixed Graphs in R. - Kayvan Sadeghi; Giovanni M. Marchetti (R J., 2012)

Graphical representation of independence structures. - Kayvan Sadeghi (2012)

β models for random hypergraphs with a given degree sequence. - Despina Stasi; Kayvan Sadeghi; Alessandro Rinaldo; Sonja Petrovic; Stephen E. Fienberg (CoRR, 2014)

On the Number of Non-Zero Elements of Joint Degree Vectors. - Éva Czabarka; Johannes Rauh; Kayvan Sadeghi; Taylor Short; László A. Székely (Electron. J. Comb., 2017)

Faithfulness of Probability Distributions and Graphs. - Kayvan Sadeghi (J. Mach. Learn. Res., 2017)

Markov Properties of Discrete Determinantal Point Processes. - Kayvan Sadeghi; Alessandro Rinaldo (AISTATS, 2019)

Conditions and Assumptions for Constraint-based Causal Structure Learning. - Kayvan Sadeghi; Terry Soo (J. Mach. Learn. Res., 2022)

Localised Natural Causal Learning Algorithms for Weak Consistency Conditions. - Kai Z. Teh; Kayvan Sadeghi; Terry Soo (UAI, 2024)

A General Framework for Constraint-based Causal Learning. - Kai Z. Teh; Kayvan Sadeghi; Terry Soo (CoRR, 2024)

Causal Models for Growing Networks. - Gecia Bravo Hermsdorff; Kayvan Sadeghi; Lee M. Gunderson (UAI, 2025)