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Causal Inference



Causal inference is a challenging and promising research field and its application to domains such as climate science will have a high impact both to advance science and to address topics of critical importance for the society. The core methodological topics include causal inference and causal discovery for spatio-temporal dynamical systems, machine learning, deep learning, and nonlinear time series analysis.

 

 

 

 

Start/End:

2017/---

Project Leader:

Jakob Runge, Andreas Gerhardus


Current Projects
CausalAnomalies
CausalEarth
XAIDA
iMIRACLI
CausalFlood
Causal Inference
Related Topics
Cybernetics, Artificial Intelligence and Robotics
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