rpatrik96/nl-causal-representations
This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (particularly, with Nonlinear ICA) can be used to extract the causal graph from an underlying structural equation model (SEM).
PythonMIT
Stargazers
- 2019mohamedProteinea
- aliizadiVancouver, CA
- BrentKylling
- denisfitz57
- drewwilimitisVanderbilt University
- jbdatascienceNetherlands
- Julian-Nguyen
- kunwuz
- MaheepChaudharyNanyang Technological University
- pablormierHeidelberg University
- rudolfwilliamMax Planck Institute for Intelligent Systems
- stes@dynamical-inference @ki-macht-schule @kinematik-ai
- till2Hasso-Plattner-Institute
- TsarpfHelsinki
- vishalbelsare
- ZWQ-785915792