Author

E. S. Schaffer

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Animal Behavior & Cognition· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Assay:imaging· 2 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Organism:mouse· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

A. Wu· 2 shared E. K. Buchanan· 2 shared L. Paninski· 2 shared M. R. Whiteway· 2 shared N. Mishra· 2 shared A. Norovich· 1 shared C. D. Salzman· 1 shared C. Everett· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersAnimal Behavior & Cognition

A. Wu

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2 papers

Recent·Most cited

Semi-supervised sequence modeling for improved behavioral segmentation

M. R. Whiteway, E. S. Schaffer, A. Wu, E. K. Buchanan, O. F. Onder, N. Mishra, L. Paninski

This paper introduces a semi-supervised sequence model for behavioral segmentation that combines supervised, weakly supervised, and self-supervised losses to improve accuracy with sparse labels.

bioRxiv · Jun 16, 2021 · PreprintAnimal Behavior & Cognition

Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking

A. Wu, E. K. Buchanan, M. R. Whiteway, M. Schartner, G. T. Meijer, J.-P. Noel, E. Rodriguez, C. Everett, A. Norovich, E. S. Schaffer, N. Mishra, C. D. Salzman, D. E. Angelaki, T. International Brain Laboratory, J. P. Cunningham, L. Paninski

This paper introduces a semi-supervised deep graphical model for animal pose tracking that improves accuracy by leveraging spatial and temporal constraints in behavioral videos.

bioRxiv · Aug 20, 2020 · PreprintAnimal Behavior & Cognition