Research map / Architectures and efficiency / RNNs and normalization
Deep Learning without Weight Transport
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use weight mirroring to learn feedback weights without weight transport | ResNet-18 · ImageNet | top-1 test error: 97.4(2)% -> 30.2(7)% | Helped |
| Use reciprocal Kolen-Pollack learning to learn feedback weights | ResNet-18 · ImageNet | top-1 test error: 97.4(2)% -> 29.2(4)% | Helped |
| Use weight mirroring to learn feedback weights without weight transport | ResNet-50 · ImageNet | top-1 test error: 98.9(1)% -> 23.4(5)% | Helped |
| Use reciprocal Kolen-Pollack learning to learn feedback weights | ResNet-50 · ImageNet | top-1 test error: 98.9(1)% -> 23.9(7)% | Helped |
| Apply BatchNorm before ReLU rather than after it | Sign-symmetry · ImageNet, ResNet-18 | top-1 test error: 39.2(4)% -> 37.8(4)% | Helped |
| Apply BatchNorm before ReLU rather than after it | Sign-symmetry · ImageNet, ResNet-50 | top-1 test error: 33.8(3)% -> 32.6(6)% | Helped |
| Apply BatchNorm before ReLU rather than after it | Backprop, feedback alignment, Kolen-Pollack, and weight mirror · ImageNet | top-1 test error | No clear effect |
Closest papers by meaning
- One-Time Soft Alignment Enables Resilient Learning without Weight Transport (NeurIPS 2026 · similarity 0.89)
- Pretraining with Random Noise for Fast and Robust Learning without Weight Transport (NeurIPS 2024 · similarity 0.86)
- Improving equilibrium propagation without weight symmetry through Jacobian homeostasis (ICLR 2024 · similarity 0.84)
- The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks (ICML 2024 · similarity 0.84)
- Improving Deep Learning Speed and Performance Through Synaptic Neural Balance (AAAI 2025 · similarity 0.84)
- Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks (ICML 2024 · similarity 0.84)
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