https://github.com/fededagos/celltypes-classification
Source code for the dissertation "Deep Learning Approaches Towards Semi-Supervised Cell Type Classification in Cerebellar Neuropixels Recordings" submitted as requirement of the MSc in Machine Learning at UCL
https://github.com/fededagos/celltypes-classification
deep-learning machine-learning neuroscience pyro pytorch semi-supervised-learning variational-autoencoder
Last synced: about 1 month ago
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Source code for the dissertation "Deep Learning Approaches Towards Semi-Supervised Cell Type Classification in Cerebellar Neuropixels Recordings" submitted as requirement of the MSc in Machine Learning at UCL
- Host: GitHub
- URL: https://github.com/fededagos/celltypes-classification
- Owner: fededagos
- Created: 2022-09-10T12:44:37.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-10-29T16:38:23.000Z (over 3 years ago)
- Last Synced: 2025-01-26T12:44:58.200Z (over 1 year ago)
- Topics: deep-learning, machine-learning, neuroscience, pyro, pytorch, semi-supervised-learning, variational-autoencoder
- Language: Jupyter Notebook
- Homepage:
- Size: 38.3 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Deep Learning Approaches Towards Semi-Supervised Cell Type Classification in Cerebellar Neuropixels Recordings
Source code for the homonymous dissertation submitted as part requirement for the MSc Machine Learning at UCL.
Full text dissertation available for download [here](https://files.fededagos.me/COMP0091_Dagostino.pdf).
The **cerebellum dataset** on which all experiments are based can be downloaded [here](https://files.fededagos.me/datasets/cerebellum_dataset.h5).
To correctly replicate the experiments, download the dataset and place it in your root directory.
Details on the the exact python environment used to run the experiments are in `environment.yml`.
Minimum requirements are in `requirements.txt`