AINeutralarXiv – CS AI · 7h ago6/10
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Neural Network Compression by Approximate Differential Equivalence
Researchers propose a novel neural network compression method using polynomial ODE systems and Approximate Forward Differential Equivalence to aggregate neurons with similar functional behavior, rather than pruning weights independently. The approach achieves significant parameter reduction while maintaining accuracy, outperforming traditional magnitude-based pruning methods across synthetic and public benchmarks.