65 citations · 156 across the 21 of their papers we have counts for
5 papers · 1 filter
Interpretable Causal Graphical Models for Equilibrium Systems with Confounding
Kai Z. Teh, Kayvan Sadeghi, Terry Soo
In applications, quantities of interest are often modelled in equilibrium or an equilibrium solution is sought. The presence of confounding makes causal inference in this setting c…
Towards Robust Causal Effect Identification Beyond Markov Equivalence
Kai Z. Teh, Kayvan Sadeghi, Terry Soo
Causal effect identification typically requires a fully specified causal graph, which can be difficult to obtain in practice. We provide a sufficient criterion for identifying caus…
Localised Natural Causal Learning Algorithms for Weak Consistency Conditions
Kai Z Teh, Kayvan Sadeghi, Terry Soo
By relaxing conditions for natural structure learning algorithms, a family of constraint-based algorithms containing all exact structure learning algorithms under the faithfulness…
Hierarchical Models for Independence Structures of Networks
Kayvan Sadeghi, Alessandro Rinaldo
We introduce a new family of network models, called hierarchical network models, that allow us to represent in an explicit manner the stochastic dependence among the dyads (random…
Sequences of regressions and their independences
Nanny Wermuth, Kayvan Sadeghi
Ordered sequences of univariate or multivariate regressions provide statistical models for analysing data from randomized, possibly sequential interventions, from cohort or multi-w…