3 papers
cs.AI2026
Relational Structural Causal Models
Adiba Ejaz, Elias Bareinboim
An artificial intelligence must have a model of its environment that is causal, supporting reasoning about interventions and counterfactuals, and also combinatorial, supporting gen…
cs.LG2025
Less Greedy Equivalence Search
Adiba Ejaz, Elias Bareinboim
Greedy Equivalence Search (GES) is a classic score-based algorithm for causal discovery from observational data. In the sample limit, it recovers the Markov equivalence class of gr…
cs.LG2025
Testing Causal Models with Hidden Variables in Polynomial Delay via Conditional Independencies
Hyunchai Jeong, Adiba Ejaz, Jin Tian +1
Testing a hypothesized causal model against observational data is a key prerequisite for many causal inference tasks. A natural approach is to test whether the conditional independ…