HCL-FF augments the Forward-Forward algorithm with hierarchical learning and contrastive objectives to reach new state-of-the-art accuracies among FF methods on CIFAR-10 (+5.46%), CIFAR-100 (+17.00%), and Tiny-ImageNet (+12.51%).
Forward learning with top-down feedback: Empirical and analytical characterization.arXiv preprint arXiv:2302.05440, 2023
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HCL-FF: Hierarchical and Contrastive Learning for Forward-Forward Algorithm
HCL-FF augments the Forward-Forward algorithm with hierarchical learning and contrastive objectives to reach new state-of-the-art accuracies among FF methods on CIFAR-10 (+5.46%), CIFAR-100 (+17.00%), and Tiny-ImageNet (+12.51%).