Hi, the spikingjelly is really good and easy to use. One advice is do you consider integrating some Brain-like properties such as STDP in this library? Maybe it's a good way to add the advantage of spikingjelly.
While #269 added additional functions to pull and subsequently access delayed neuron variables, this isn't done for pre and postsynaptic variables associated with weight update models. This would be pretty trivial and would essentially involve copying this logic into the loops [here](https:/
What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail.
CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail.
TUM Master’s thesis: Steering a robot with an event-based vision sensor in a lane-keeping task using methods such as Deep Reinforcement Learning or Spiking Neural Networks.
Following the merge of the adjoint code, our coverage fell dramatically. We should put in some effort to get it back to 100%! :-)