Coordinate-VAE: Unsupervised Clustering and De-Noising of Peripheral Nervous System Data
Abstract
The peripheral nervous system represents the input/output system for the brain. Cuff electrodes implanted on the peripheral nervous system allow observation and control over this system, however, the data produced by these electrodes have a low signal-to-noise ratio and a complex signal content. In this paper, we consider the analysis of neural data recorded from the vagus nerve in animal models, and develop an unsupervised learner based on convolutional neural networks that is able to simultaneously de-noise and cluster regions of the data by signal content.
Cite
Text
Hardcastle et al. "Coordinate-VAE: Unsupervised Clustering and De-Noising of Peripheral Nervous System Data." NeurIPS 2019 Workshops: Neuro_AI, 2019.Markdown
[Hardcastle et al. "Coordinate-VAE: Unsupervised Clustering and De-Noising of Peripheral Nervous System Data." NeurIPS 2019 Workshops: Neuro_AI, 2019.](https://mlanthology.org/neuripsw/2019/hardcastle2019neuripsw-coordinatevae/)BibTeX
@inproceedings{hardcastle2019neuripsw-coordinatevae,
title = {{Coordinate-VAE: Unsupervised Clustering and De-Noising of Peripheral Nervous System Data}},
author = {Hardcastle, Thomas J and Lee, Susannah and Wernisch, Lorenz and Fortier-Poisson, Pascal and Shunmugam, Sudha and Hewage, Kalon and Edwards, Tris and Armitage, Oliver and Hewage, Emil},
booktitle = {NeurIPS 2019 Workshops: Neuro_AI},
year = {2019},
url = {https://mlanthology.org/neuripsw/2019/hardcastle2019neuripsw-coordinatevae/}
}