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

21 Feb 2020Sebastian WeichwaldMartin E JakobsenPhillip B MogensenLasse PetersenNikolaj ThamsGherardo Varando

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... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.