Search Results for author: Taiga Abe

Found 4 papers, 3 papers with code

Deep Ensembles Work, But Are They Necessary?

1 code implementation14 Feb 2022 Taiga Abe, E. Kelly Buchanan, Geoff Pleiss, Richard Zemel, John P. Cunningham

While deep ensembles are a practical way to achieve improvements to predictive power, uncertainty quantification, and robustness, our results show that these improvements can be replicated by a (larger) single model.

Uncertainty Quantification

Pathologies of Predictive Diversity in Deep Ensembles

no code implementations1 Feb 2023 Taiga Abe, E. Kelly Buchanan, Geoff Pleiss, John P. Cunningham

Here we demonstrate that these intuitions do not apply to high-capacity neural network ensembles (deep ensembles), and in fact the opposite is often true.

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