Covariance-aware goodness and auxiliary modules let Forward-Forward training scale to 16-layer networks, achieving 73.01% on ImageNet-100 and 50.30% on Tiny-ImageNet with roughly half the peak memory of backpropagation.
Proceedings of the 39th International Conference on Machine Learning , series =
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Covariance-Aware Goodness for Scalable Forward-Forward Learning
Covariance-aware goodness and auxiliary modules let Forward-Forward training scale to 16-layer networks, achieving 73.01% on ImageNet-100 and 50.30% on Tiny-ImageNet with roughly half the peak memory of backpropagation.