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| author | YurenHao0426 <Blackhao0426@gmail.com> | 2026-04-01 09:54:31 -0500 |
|---|---|---|
| committer | YurenHao0426 <Blackhao0426@gmail.com> | 2026-04-01 09:54:31 -0500 |
| commit | a0ec1a6c17b72a3ab769fb8c12f5ef381f38beed (patch) | |
| tree | ff2ac49bd3747b328e676c961b40622c747b2f3d /report_explore | |
| parent | a002f03804fb67ed2489eb4c1229db41e0126514 (diff) | |
Add BP support sparsity analysis: threshold sweep + gradient histograms
A1 Synthetic: all methods have >93% support at τ=1e-6 (gradients rarely zero)
A2 CIFAR: massive gap — BP 98.4% vs DFA 0.4% vs SB 21% vs CB 3%
DFA-trained CIFAR networks have near-zero BP gradients for 99.6% of samples
This explains why Gamma is unreliable for CIFAR non-BP methods
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Diffstat (limited to 'report_explore')
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