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Research map / Architectures and efficiency / RNNs and normalization

Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks

NeurIPS 2019 · Architectures and efficiency › RNNs and normalization · approach: Hebbian and predictive coding · 2 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Increase neurons per site from 4 to 100 (ablation)Structured similarity matching · MNIST testclassification error (%): 3.87 -> 1.40Helped
Increase neurons per site from 64 to 100 (ablation)Structured similarity matching · MNIST testclassification error (%): 1.47 -> 1.40Helped
Use NPS 100 instead of the biologically plausible training baselineMNIST classification · MNISTclassification error (%): 1.46% -> 1.40Helped

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