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researcher

Karl Kumbier

4 papers hereh-index 92.5k citations18 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • stat.ML3
  • stat.AP1

identity via Semantic Scholar / OpenAlex

activity
20172020
most citedArtificial Intelligence and Statistics

358 citations · 358 across the 1 of their papers we have counts for

collaborators

4 papers

stat.AP2020

Curating a COVID-19 data repository and forecasting county-level death counts in the United States

Nick Altieri, Rebecca L. Barter, James Duncan +11

As the COVID-19 outbreak evolves, accurate forecasting continues to play an extremely important role in informing policy decisions. In this paper, we present our continuous curatio…

stat.ML2019

A Debiased MDI Feature Importance Measure for Random Forests

Xiao Li, Yu Wang, Sumanta Basu +2

Tree ensembles such as Random Forests have achieved impressive empirical success across a wide variety of applications. To understand how these models make predictions, people rout…

stat.ML2019

Interpretable machine learning: definitions, methods, and applications

W. James Murdoch, Chandan Singh, Karl Kumbier +2

Machine-learning models have demonstrated great success in learning complex patterns that enable them to make predictions about unobserved data. In addition to using models for pre…

stat.ML2017★ 358 cited

Artificial Intelligence and Statistics

Bin Yu, Karl Kumbier

Artificial intelligence (AI) is intrinsically data-driven. It calls for the application of statistical concepts through human-machine collaboration during generation of data, devel…

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