no code implementations • 20 Dec 2023 • Eric Rawls, Bryan Andrews, Kelvin Lim, Erich Kummerfeld
Designing studies that apply causal discovery requires navigating many researcher degrees of freedom.
1 code implementation • 26 Oct 2023 • Bryan Andrews, Joseph Ramsey, Ruben Sanchez-Romero, Jazmin Camchong, Erich Kummerfeld
However, the accuracy and execution time of learning algorithms generally struggle to scale to problems with hundreds of highly connected variables -- for instance, recovering brain networks from fMRI data.
1 code implementation • 23 Feb 2022 • Andrew Colt Deckert, Erich Kummerfeld
Binning (a. k. a.
no code implementations • 3 Jun 2021 • Ju Sun, Le Peng, Taihui Li, Dyah Adila, Zach Zaiman, Genevieve B. Melton, Nicholas Ingraham, Eric Murray, Daniel Boley, Sean Switzer, John L. Burns, Kun Huang, Tadashi Allen, Scott D. Steenburg, Judy Wawira Gichoya, Erich Kummerfeld, Christopher Tignanelli
Conclusions and Relevance: AI-based diagnostic tools may serve as an adjunct, but not replacement, for clinical decision support of COVID-19 diagnosis, which largely hinges on exposure history, signs, and symptoms.
no code implementations • 4 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.
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.