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  1. SAT-based causal discovery under weaker assumptions. Zhalama, Jiji Zhang, Frederick Eberhardt & Wolfgang Mayer - 2017 - In Zhalama, Jiji Zhang, Frederick Eberhardt & Wolfgang Mayer (eds.), Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI). Association for Uncertainty in Artificial Intelligence (AUAI).
    Using the flexibility of recently developed methods for causal discovery based on Boolean satisfiability solvers, we encode a variety of assumptions that weaken the Faithfulness assumption. The encoding results in a number of SAT-based algorithms whose asymptotic correctness relies on weaker conditions than are standardly assumed. This implementation of a whole set of assumptions in the same platform enables us to systematically explore the effect of weakening the Faithfulness assumption on causal discovery. An important effect, suggested by simulation results, is (...)
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  • The three faces of faithfulness.Jiji Zhang & Peter Spirtes - 2016 - Synthese 193 (4):1011-1027.
    In the causal inference framework of Spirtes, Glymour, and Scheines, inferences about causal relationships are made from samples from probability distributions and a number of assumptions relating causal relations to probability distributions. The most controversial of these assumptions is the Causal Faithfulness Assumption, which roughly states that if a conditional independence statement is true of a probability distribution generated by a causal structure, it is entailed by the causal structure and not just for particular parameter values. In this paper we (...)
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  • The Evaluation of Discovery: Models, Simulation and Search through “Big Data”.Kun Zhang, Joseph D. Ramsey & Clark Glymour - 2019 - Open Philosophy 2 (1):39-48.
    A central theme in western philosophy was to find formal methods that can reliably discover empirical relationships and their explanations from data assembled from experience. As a philosophical project, that ambition was abandoned in the 20th century and generally dismissed as impossible. It was replaced in philosophy by neo-Kantian efforts at reconstruction and justification, and in professional statistics by the more limited ambition to estimate a small number of parameters in pre-specified hypotheses. The influx of “big data” from climate science, (...)
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  • The Frugal Inference of Causal Relations.Malcolm Forster, Garvesh Raskutti, Reuben Stern & Naftali Weinberger - 2018 - British Journal for the Philosophy of Science 69 (3):821-848.
    Recent approaches to causal modelling rely upon the causal Markov condition, which specifies which probability distributions are compatible with a directed acyclic graph. Further principles are required in order to choose among the large number of DAGs compatible with a given probability distribution. Here we present a principle that we call frugality. This principle tells one to choose the DAG with the fewest causal arrows. We argue that frugality has several desirable properties compared to the other principles that have been (...)
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