SbS Extension for PyTorch
C++ | ||
DATA_CIFAR10 | ||
DATA_FASHION_MNIST | ||
DATA_MNIST | ||
Dataset.py | ||
learn_it.py | ||
LICENSE | ||
Parameter.py | ||
PyHDynamicCNNManyIP.pyi | ||
PySpikeGeneration2DManyIP.pyi | ||
README.md | ||
SbS.py |
pytorch-sbs
SbS Extension for PyTorch
Based on the scientific papers:
Back-Propagation Learning in Deep Spike-By-Spike Networks
David Rotermund and Klaus R. Pawelzik
Front. Comput. Neurosci., https://doi.org/10.3389/fncom.2019.00055
https://www.frontiersin.org/articles/10.3389/fncom.2019.00055/full
Efficient Computation Based on Stochastic Spikes
Udo Ernst, David Rotermund, and Klaus Pawelzik
Neural Computation (2007) 19 (5): 1313–1343.
https://direct.mit.edu/neco/article-abstract/19/5/1313/7183/Efficient-Computation-Based-on-Stochastic-Spikes