Search Results for author: Erich Kummerfeld

Found 4 papers, 1 papers with code

Simulations evaluating resampling methods for causal discovery: ensemble performance and calibration

no code implementations4 Oct 2019 Erich Kummerfeld, Alexander Rix

One of the major hurdles preventing the field of causal discovery from having a larger impact is that it is difficult to determine when the output of a causal discovery method can be trusted in a real-world setting.

Causal Discovery

Tracking Time-varying Graphical Structure

no code implementations NeurIPS 2013 Erich Kummerfeld, David Danks

Structure learning algorithms for graphical models have focused almost exclusively on stable environments in which the underlying generative process does not change; that is, they assume that the generating model is globally stationary.

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