Pathologies of Predictive Diversity in Deep Ensembles

no code implementations • 1 Feb 2023 • Taiga Abe, E. Kelly Buchanan, Geoff Pleiss, John P. Cunningham

Here we demonstrate that this intuition does not carry over to ensembles of deep neural networks used for classification, and in fact the opposite can be true.

Deep Ensembles Work, But Are They Necessary?

1 code implementation • 14 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.

BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos

1 code implementation • NeurIPS 2019 • Eleanor Batty, Matthew Whiteway, Shreya Saxena, Dan Biderman, Taiga Abe, Simon Musall, Winthrop Gillis, Jeffrey Markowitz, Anne Churchland, John P. Cunningham, Sandeep R. Datta, Scott Linderman, Liam Paninski

Here we introduce a probabilistic framework for the analysis of behavioral video and neural activity.

Markerless tracking of user-defined features with deep learning

1 code implementation • 9 Apr 2018 • Alexander Mathis, Pranav Mamidanna, Taiga Abe, Kevin M. Cury, Venkatesh N. Murthy, Mackenzie W. Mathis, Matthias Bethge

Quantifying behavior is crucial for many applications in neuroscience.

Animal Pose Estimation Transfer Learning