Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders.

Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders.

Recent neuroscience studies demonstrate that a deeper understanding of brain function requires a deeper understanding of behavior. Detailed behavioral measurements are now often collected using video cameras, resulting in an increased need for computer vision algorithms that extract useful informati...

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Bibliographic Details
Main Authors: Matthew R Whiteway, Dan Biderman, Yoni Friedman, Mario Dipoppa, E Kelly Buchanan, Anqi Wu, John Zhou, Niccolò Bonacchi, Nathaniel J Miska, Jean-Paul Noel, Erica Rodriguez, Michael Schartner, Karolina Socha, Anne E Urai, C Daniel Salzman, International Brain Laboratory, John P Cunningham, Liam Paninski
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-09-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1009439

Internet

https://doi.org/10.1371/journal.pcbi.1009439

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