30 citations · 49 across the 4 of their papers we have counts for
4 papers
Pathologies of Predictive Diversity in Deep Ensembles
Taiga Abe, E. Kelly Buchanan, Geoff Pleiss +1
Classic results establish that encouraging predictive diversity improves performance in ensembles of low-capacity models, e.g. through bagging or boosting. Here we demonstrate that…
Deep Ensembles Work, But Are They Necessary?
Taiga Abe, E. Kelly Buchanan, Geoff Pleiss +2
Ensembling neural networks is an effective way to increase accuracy, and can often match the performance of individual larger models. This observation poses a natural question: giv…
Chronic, cortex-wide imaging of specific cell populations during behavior
Joao Couto, Simon Musall, Xiaonan R Sun +8
Measurements of neuronal activity across brain areas are important for understanding the neural correlates of cognitive and motor processes like attention, decision-making, and act…
Markerless tracking of user-defined features with deep learning
Alexander Mathis, Pranav Mamidanna, Taiga Abe +4
Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, y…