Synthetic trained dense-layer weights --- Xavier init plus 50 momentum-smoothed gradient updates, L1-like shrinkage of small weights, and heavy-tailed outliers. An *untrained* layer is i.i.d. Gaussian (indistinguishable from noise); training imprints local correlation.
Standard analysis sees: aperiodic / broadband; high-complexity (noise-like). The atlas detects no named structure beyond this.
Nothing beyond the standard reading — this source’s structure is already captured by standard features; the atlas adds no named residual.
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_(centered)/signed_log_z/Neural_Net_(Dense).png)
_(centered)/xy_path/Neural_Net_(Dense).png)
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/barcode/Neural_Net_(Dense).png)
/d_curve/Neural_Net_(Dense).png)
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/phi_spectrum/Neural_Net_(Dense).png)
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/default/Neural_Net_(Dense).png)
/default/Neural_Net_(Dense).png)
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| Nearest neighbor | Distance | |
|---|---|---|
| Gaussian Noise | 2.70 | cross-domain |
| Entanglement Entropy | 3.08 | cross-domain |
| Poisson Counts | 3.50 | cross-domain |
This source does not rank extreme on any metric.