Corpus ID: 211259094

Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values

@article{Weichwald2020CausalSL,
  title={Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values},
  author={Sebastian Weichwald and Martin Emil Jakobsen and Phillip B Mogensen and Lasse Petersen and Nikolaj Thams and Gherardo Varando},
  journal={ArXiv},
  year={2020},
  volume={abs/2002.09573}
}
  • Sebastian Weichwald, Martin Emil Jakobsen, +3 authors Gherardo Varando
  • Published in ArXiv 2020
  • Mathematics, Computer Science
  • In this article, we describe the algorithms for causal structure learning from time series data that won the Causality 4 Climate competition at the Conference on Neural Information Processing Systems 2019 (NeurIPS). We examine how our combination of established ideas achieves competitive performance on semi-realistic and realistic time series data exhibiting common challenges in real-world Earth sciences data. In particular, we discuss a) a rationale for leveraging linear methods to identify… CONTINUE READING

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