most citedData Generating Process to Evaluate Causal Discovery Techniques for Time Series Data

8 citations · 9 across the 2 of their papers we have counts for

collaborators

3 papers

stat.ML2022★ 1 cited

Causal Analysis of the TOPCAT Trial: Spironolactone for Preserved Cardiac Function Heart Failure

Francesca E. D. Raimondi, Tadhg O'Keeffe, Hana Chockler +6

We describe the results of applying causal discovery methods on the data from a multi-site clinical trial, on the Treatment of Preserved Cardiac Function Heart Failure with an Aldo…

stat.ML2021★ 8 cited

Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data

Andrew R. Lawrence, Marcus Kaiser, Rui Sampaio +1

Going beyond correlations, the understanding and identification of causal relationships in observational time series, an important subfield of Causal Discovery, poses a major chall…

stat.ML2021

Unsuitability of NOTEARS for Causal Graph Discovery

Marcus Kaiser, Maksim Sipos

Causal Discovery methods aim to identify a DAG structure that represents causal relationships from observational data. In this article, we stress that it is important to test such…