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  • Limited to the following ingredients: * data * include/exclude edges Not in scope (but definitely in the backlog): * Bayesian priors -- these would need a causal prior * Mechanism constraints -- these would require an SCM learner that can use these constraints.

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  • Implement basic score-based causal discovery. * This entails a score-based greedy search structure learning algorithm * Modifying the score to account for interventions (which turns structure learning into causal discovery) * Equivalence classes that represent interventions * Validation on a basic dataset

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    2/6 issues closed