A PyTorch-based framework for developing and training Spiking Neural Networks (SNNs).
SpikingJelly provides a user-friendly Python environment for researchers and developers working with SNNs. It supports advanced features like ANN2SNN conversion, event-based datasets, and acceleration backends such as CuPy and Triton, enabling efficient large-scale SNN model development.
A PyTorch-based framework for developing and training Spiking Neural Networks (SNNs).
Machine learning engineers and researchers focused on Spiking Neural Networks and event-driven AI.
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