971 citations · 1.6k across the 23 of their papers we have counts for
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stat.ML2023★ 2 cited
Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery
Saranya Ganesh S., Tom Beucler, Frederick Iat-Hin Tam +3
Robust feature selection is vital for creating reliable and interpretable Machine Learning (ML) models. When designing statistical prediction models in cases where domain knowledge…
stat.ML2017★ 37 cited
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information
Jakob Runge
Conditional independence testing is a fundamental problem underlying causal discovery and a particularly challenging task in the presence of nonlinear and high-dimensional dependen…
stat.ML2015★ 43 cited
Optimal model-free prediction from multivariate time series
Jakob Runge, Reik V. Donner, Jürgen Kurths
Forecasting a time series from multivariate predictors constitutes a challenging problem, especially using model-free approaches. Most techniques, such as nearest-neighbor predicti…