snntorch
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jeshraghian
Deep and online learning with spiking neural networks in Python
I was wondering if anyone had used snnTorch for regression, and perhaps how you set your networks up. Just looking for simple, general examples! MSELoss would likely be the type...
### Description the `inhibition` argument of neurons is only setup for single dimensional channels / outputs of nn.Linear It does not work for convolutional layers. The way I see it,...
Apply on/off target weighting to `snntorch.functional` losses in the same way the PyTorch enables weighting. Cross Entropy-based losses should be straightforward; Mean Square Error Losses are less trivial.
SConv2dLSTM currently concatenates the hidden cell with the input cell, applies a single nn.Conv2d function of channel length 4*out_channel The output is then split into 4 chunks (along the channel...
Enable user to pass in state equations, to specify the state variable(s), and custom neuron class is automatically generated which can be treated like any other LIF neuron.
Enable user to pass in an arbitrary function which is automatically centered about the firing threshold.
* Add gated spiking units with learnable delay times * Integrate it with each LIF neuron
* Implement forward-mode AD for temporal connections; reverse-mode AD for layer connections * Update at each time step * Approximate BPTT without having to store any historical gradients
* currently, the initialization of state variables step is only equipped for one common time step possible solutions: * modifying the init step to adjust to the input first dimension...
Add an adaptive, time-varying threshold to all neuron models. * threshold should decay back to steady-state value over some time-constant * threshold may need to saturate to some value to...
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Deep and online learning with spiking neural networks in Python