Brain-Inspired Pruning Cuts Neural Networks By 90%
Brain-inspired pruning method cuts Neural Networks by 90% without losing accuracy, using criticality theory to identify important neurons and adaptively prune less useful ones.
This is a Plain English Papers summary of a research paper called Brain-Inspired Method Cuts Neural Networks by 90% Without Losing Accuracy. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter. Overview Novel brain-inspired pruning method for Spiking Neural Networks (SNNs) Uses criticality theory from neuroscience to identify important neurons Achieves up to 90% network compression while maintaining accuracy Introduces adaptive pruning schedule based on network dynamics Demonstrates effectiveness across multiple SNN architectures Plain E...