An auto generator of alternative representations for Bayesian Networks.
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Updated
Nov 23, 2018 - Python
An auto generator of alternative representations for Bayesian Networks.
Investigation of network geometry and percolation in directed acyclic graphs (MSci Thesis). Maintained by Ariel Flint Ashery and Kevin Teo. Supervisor: Timothy Evans
Causal Abstraction of Neural Models Trained to Solve ReaSCAN
A Python package for learning and using causal networks via discrete geometry
Code accompanying my 2021 ASA SDSS paper
A Python package for drug discovery by analyzing causal paths on multiscale networks
Causing: CAUsal INterpretation using Graphs
A Python library that helps data scientists to infer causation rather than observing correlation.
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