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

Whiteway, M. R., Biderman, D., Friedman, Y., Dipoppa, M., Buchanan, E. K., Wu, A., Zhou, J., Bonacchi, N., Miska, N. J., Noel, J.-P., Rodriguez, E., Schartner, M., Socha, K., Urai, A. E., Salzman, C. D., Cunningham, J. P., & Paninski, L. (2021). Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders. PLOS Computational Biology, 17(9), e1009439. https://doi.org/10.1371/journal.pcbi.1009439
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
John P. Cunningham
Liam Paninski
Affiliated Authors:
Matthew R. Whiteway
Dan Biderman
Yoni Friedman
Mario Dipoppa
E. Kelly Buchanan
Anqi Wu
John Zhou
Erica Rodriguez
C. Daniel Salzman
John P. Cunningham
Liam Paninski
Publication Type:
Article
Unique ID:
10.1371/journal.pcbi.1009439
PMID:
Publication Date:
Data Source:
Scopus

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