1 code implementation • 27 Sep 2021 • Saeed Reza Kheradpisheh, Maryam Mirsadeghi, Timothée Masquelier
By assuming IF neuron with rate-coding as an approximation of ReLU, we backpropagate the error of the SNN in the proxy ANN to update the shared weights, simply by replacing the ANN final output with that of the SNN.
no code implementations • 31 Aug 2021 • Maryam Mirsadeghi, Majid Shalchian, Saeed Reza Kheradpisheh, Timothée Masquelier
To do so, we consider a convolutional SNN (CSNN) with two sets of weights: real-valued weights that are updated in the backward pass and their signs, binary weights, that are employed in the feedforward process.
Ranked #11 on Image Classification on Fashion-MNIST
1 code implementation • 8 Jul 2020 • Saeed Reza Kheradpisheh, Maryam Mirsadeghi, Timothée Masquelier
We recently proposed the S4NN algorithm, essentially an adaptation of backpropagation to multilayer spiking neural networks that use simple non-leaky integrate-and-fire neurons and a form of temporal coding known as time-to-first-spike coding.