Author

Jasmine Collins

Google (United States)

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Neuroscience· 1

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Organism:human· 1 Organism:mouse· 1 Assay:spatial transcriptomics· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Chethan PandarinathiD· 1 shared Daniel J. O’SheaiD· 1 shared David SussilloiD· 1 shared Eric M. TrautmanniD· 1 shared Jaimie M. HendersoniD· 1 shared Jonathan C. KaoiD· 1 shared K.V. ShenoyiD· 1 shared Larry F. AbbottiD· 1 shared

Activity by Year

2018-2018 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperNeuroscience

Chethan PandarinathORCID

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1 paper

Recent·Most cited

Inferring single-trial neural population dynamics using sequential auto-encoders

Chethan Pandarinath, Daniel J. O’Shea, Jasmine Collins, Rafał Józefowicz, Sergey D. Stavisky, Jonathan C. Kao, Eric M. Trautmann, Matthew Tyler Kaufman, Stephen I. Ryu, Leigh R. Hochberg, Jaimie M. Henderson, K.V. Shenoy, Larry F. Abbott, David Sussillo

This paper introduces LFADS, a deep learning method to infer single-trial neural population dynamics from spiking data, demonstrating improved accuracy in predicting behavior and extracting dynamics across datasets.

Nature Methods · Sep 14, 2018Peer-reviewedNeuroscience