DECOLLE is an online learning framework for spiking neural networks. The algorithmic details are described in this Frontiers paper. If you use this work in your research, please cite as:
@ARTICLE{decolle2020,
AUTHOR={Kaiser, Jacques and Mostafa, Hesham and Neftci, Emre},
TITLE={Synaptic Plasticity Dynamics for Deep Continuous Local Learning (DECOLLE)},
JOURNAL={Frontiers in Neuroscience},
VOLUME={14},
PAGES={424},
YEAR={2020},
URL={https://www.frontiersin.org/article/10.3389/fnins.2020.00424},
DOI={10.3389/fnins.2020.00424},
ISSN={1662-453X}
Clone and install. The Python setuptools will take care of dependencies
git clone https://github.com/nmi-lab/decolle-public.git
cd decolle-public
python setup.py install --user
The following will run decolle on the default parameter set
cd scripts
python train_lenet_decolle.py
All parameter sets are contained in scripts/parameters, you can use them as such:
cd scripts
python train_lenet_decolle.py --params_file=parameters/params_dvsgestures_torchneuromorphic_attention.yml
- Emre Neftci - Initial work - eneftci
- Jacques Kaiser - jackokaiser
- Massi Iacono - miacono
This project is licensed under the GPLv3 License - see the LICENSE.txt file for details
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent