Here is the code implementation of the following paper:
- A. Vosoughi, A. DSouza, A. Abidin and A. Wismüller, "Relation Discovery in Nonlinearly Related Large-Scale Settings," ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp. 5103-5107, doi: 10.1109/ICASSP43922.2022.9747356.
For the official acccess please see:
I will make the preprint available in a later time!
Climate change perhaps is one of the most challenging problems of the 21st century. The paper proposes a method to obtain causal graphical representations from the nodal recodings. The repository provides the simulation of graph inference by considering causality, which is a novel method. We show the algorithm using both synthetic networks and real-world climatology data.