Research map / Architectures and efficiency / RNNs and normalization
Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase neurons per site from 4 to 100 (ablation) | Structured similarity matching · MNIST test | classification error (%): 3.87 -> 1.40 | Helped |
| Increase neurons per site from 64 to 100 (ablation) | Structured similarity matching · MNIST test | classification error (%): 1.47 -> 1.40 | Helped |
| Use NPS 100 instead of the biologically plausible training baseline | MNIST classification · MNIST | classification error (%): 1.46% -> 1.40 | Helped |
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- Rethinking Hebbian Principle: Low-Dimensional Structural Projection for Unsupervised Learning (NeurIPS 2025 · similarity 0.86)
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