# Constraint-Based Causal Discovery In The Presence Of Cycles

@article{Mooij2020ConstraintBasedCD, title={Constraint-Based Causal Discovery In The Presence Of Cycles}, author={Joris M. Mooij and Tom Claassen}, journal={ArXiv}, year={2020}, volume={abs/2005.00610} }

While feedback loops are known to play important roles in many complex systems (for example, in economical, biological, chemical, physical, control and climatological systems), their existence is ignored in most of the causal discovery literature, where systems are typically assumed to be acyclic from the outset. When applying causal discovery algorithms designed for the acyclic setting on data generated by a system that involves feedback, one would not expect to obtain correct results, even in… Expand

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Joint Causal Inference from Multiple Contexts

- Computer Science
- J. Mach. Learn. Res.
- 2020

This work introduces Joint Causal Inference, a novel approach to causal discovery from multiple data sets from different contexts that elegantly unifies both approaches and concludes that JCI implementations can considerably outperform state-of-the-art causal discovery algorithms. Expand

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