spikingneuralnetwork
The aim of this project is to improve upon existing SNNs to make them more applicable, flexible and relevant. Can't say much more, but read here if you want to learn more: https://www.linkedin.com/pulse/bonxai-research-lab-solve-s%2525C3%2525A6b%2525C3%2525B8%3FtrackingId=Ud1ch3y8SDeKoYHXlHG1Zw%253D%253D/?trackingId=Ud1ch3y8SDeKoYHXlHG1Zw%3D%3D
Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: nature.com -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.4%) to scientific vocabulary
Repository
The aim of this project is to improve upon existing SNNs to make them more applicable, flexible and relevant. Can't say much more, but read here if you want to learn more: https://www.linkedin.com/pulse/bonxai-research-lab-solve-s%2525C3%2525A6b%2525C3%2525B8%3FtrackingId=Ud1ch3y8SDeKoYHXlHG1Zw%253D%253D/?trackingId=Ud1ch3y8SDeKoYHXlHG1Zw%3D%3D
Basic Info
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
SpikingNeuralNetwork PhD project
This project aims to replicate and expand the model developed in Zenke et al.'s 2015 article.
Disclaimer: Currently, the study is in its initial phase, developing a basic SNN model which will serve as the foundation of the model.
Install repository
git clone https://github.com/AndrlmMass/SpikingNeuralNetwork.git
Set up development environment
General
We have an environment.yml file that contains all packages to build and work with the script. Will develop a package later for testing.
Install the conda environment:
conda env create --file environment.yml
Activate the conda environment:
conda activate SNN_env_simpl
Update the environment.yml with existing env by:
conda env update --name SNN_env_simpl --file environment.yml --prune'
Noise & sleep
Navigate to the noise_analysis folder
cd noise_analysis
Install the conda environment:
conda env create --file environment.yml
Activate the conda environment:
conda activate noise_testing
Update the environment.yml with existing env by (if you add more libraries that are necessary for running the script):
conda env update --name noise_testing --file environment.yml --prune'
Owner
- Name: Andreas Lie Massey
- Login: AndrlmMass
- Kind: user
- Location: Norway
- Twitter: andreasmassey
- Repositories: 2
- Profile: https://github.com/AndrlmMass
I'm a cognitive neuroscience student at the University of Oslo.
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "SpikingNeuralNetwork"
authors:
- family-names: "Massey"
given-names: "Andreas"
abstract: "This repository improves upon existing spiking neural networks (SNNs) to make them more flexible, applicable, and relevant."
version: "1.0.0"
date-released: "2025-01-16"
url: "https://github.com/AndrImMass/SpikingNeuralNetwork"
repository-code: "https://github.com/AndrImMass/SpikingNeuralNetwork"
preferred-citation:
type: software
authors:
- family-names: "Massey"
given-names: "Andreas"
title: "SpikingNeuralNetwork"
version: "1.0.0"
url: "https://github.com/AndrImMass/SpikingNeuralNetwork"
date-released: "2025-01-16"
bibtex: |
@software{spikingneuralnetwork,
author = {Mass, AndrIm},
title = {SpikingNeuralNetwork},
year = {2025},
version = {1.0.0},
url = {https://github.com/AndrImMass/SpikingNeuralNetwork},
note = {Accessed: 2025-01-16}
}
GitHub Events
Total
- Delete event: 5
- Public event: 1
- Push event: 103
- Pull request event: 1
- Create event: 5
Last Year
- Delete event: 5
- Public event: 1
- Push event: 103
- Pull request event: 1
- Create event: 5
Dependencies
- contourpy ==1.3.0
- cycler ==0.12.1
- filelock ==3.16.1
- fonttools ==4.54.1
- fsspec ==2024.9.0
- h5py ==3.12.1
- imageio ==2.35.1
- jax ==0.4.33
- jax-cuda12-pjrt ==0.4.33
- jax-cuda12-plugin ==0.4.33
- jaxlib ==0.4.33
- jinja2 ==3.1.4
- kiwisolver ==1.4.7
- lazy-loader ==0.4
- llvmlite ==0.43.0
- markupsafe ==2.1.5
- matplotlib ==3.9.2
- ml-dtypes ==0.5.0
- mpmath ==1.3.0
- networkx ==3.3
- nir ==1.0.4
- nirtorch ==1.0
- numba ==0.60.0
- numpy ==2.0.2
- nvidia-cublas-cu12 ==12.1.3.1
- nvidia-cuda-cupti-cu12 ==12.1.105
- nvidia-cuda-nvcc-cu12 ==12.6.68
- nvidia-cuda-nvrtc-cu12 ==12.1.105
- nvidia-cuda-runtime-cu12 ==12.1.105
- nvidia-cudnn-cu12 ==9.1.0.70
- nvidia-cufft-cu12 ==11.0.2.54
- nvidia-curand-cu12 ==10.3.2.106
- nvidia-cusolver-cu12 ==11.4.5.107
- nvidia-cusparse-cu12 ==12.1.0.106
- nvidia-nccl-cu12 ==2.20.5
- nvidia-nvjitlink-cu12 ==12.6.68
- nvidia-nvtx-cu12 ==12.1.105
- opt-einsum ==3.4.0
- packaging ==24.1
- pandas ==2.2.3
- pillow ==10.4.0
- pyparsing ==3.1.4
- python-dateutil ==2.9.0.post0
- pytz ==2024.2
- scikit-image ==0.24.0
- scipy ==1.14.1
- six ==1.16.0
- snntorch ==0.9.1
- sympy ==1.13.3
- tifffile ==2024.9.20
- torch ==2.4.1
- tqdm ==4.66.5
- triton ==3.0.0
- typing-extensions ==4.12.2
- tzdata ==2024.2
- cached-property ==1.5.2
- certifi ==2024.7.4
- colorama ==0.4.6
- cycler ==0.12.1
- filelock ==3.15.4
- fonttools ==4.53.1
- fsspec ==2024.6.1
- h5py ==3.11.0
- imageio ==2.35.1
- importlib-metadata ==8.4.0
- jinja2 ==3.1.4
- joblib ==1.4.2
- kiwisolver ==1.4.5
- lazy-loader ==0.4
- matplotlib-base ==3.9.2
- networkx ==3.3
- numba ==0.60.0
- numpy ==1.26.4
- packaging ==24.1
- pandas ==2.2.2
- pillow ==10.4.0
- pip ==24.2
- pre-commit ==3.8.0
- pyparsing ==3.1.4
- python-dateutil ==2.9.0
- python-tzdata ==2024.1
- pytorch ==2.3.0
- pytz ==2024.1
- pywavelets ==1.7.0
- scikit-image ==0.24.0
- scikit-learn ==1.5.1
- scipy ==1.14.1
- setuptools ==72.2.0
- six ==1.16.0
- snntorch ==0.9.1
- sympy ==1.13.2
- threadpoolctl ==3.5.0
- tifffile ==2024.8.24
- tqdm ==4.66.5
- typing_extensions ==4.12.2
- wheel ==0.44.0
- zipp ==3.20.1