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Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience
Emily L. Mackevicius, Andrew H. Bahle, Alex H. Williams, Shijie Gu, Natalia I. Denissenko, Mark S. Goldman, Michale S. Fee
doi: https://doi.org/10.1101/273128
Emily L. Mackevicius
1McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT
Andrew H. Bahle
1McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT
Alex H. Williams
2Neurosciences Program, Stanford University, Stanford, CA, 94305
Shijie Gu
1McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT
3School of Life Sciences and Technology, ShanghaiTech University
Natalia I. Denissenko
1McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT
Mark S. Goldman
4Center for Neuroscience, Department of Neurobiology, Physiology and Behavior, Department of Ophthamology and Vision Science, UC Davis
Michale S. Fee
1McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT
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Posted December 23, 2018.
Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience
Emily L. Mackevicius, Andrew H. Bahle, Alex H. Williams, Shijie Gu, Natalia I. Denissenko, Mark S. Goldman, Michale S. Fee
bioRxiv 273128; doi: https://doi.org/10.1101/273128
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