A Python library that helps data scientists to infer causation rather than observing correlation.
Causing: CAUsal INterpretation using Graphs
A Python package for drug discovery by analyzing causal paths on multiscale networks
Implementation of Causation Entropy from Clarkson Center for Complex Systems Science (C3S2)
Code accompanying my 2021 ASA SDSS paper
Causal Abstraction of Neural Models Trained to Solve ReaSCAN
Investigation of network geometry and percolation in directed acyclic graphs (MSci Thesis). Maintained by Ariel Flint Ashery and Kevin Teo. Supervisor: Timothy Evans
A Python package for learning and using causal networks via discrete geometry
An auto generator of alternative representations for Bayesian Networks.
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