Giorgio Gilestro
ab3dc10587
- paper/pnas -> paper/manuscript (venue-neutral)
- configs/layer1 -> configs/inheritance, src/knowledge -> src/inheritance
(imported as `inheritance`), make layer1 -> make inheritance; layer2 alias dropped
- inheritance and trained-network bundles named after the manuscript figure
they feed (fig2_grounding_sweep, figS3_rebaselining, ...), or descriptively
where they feed none; configs keep their `experiment:` value so parquet
hashes are unchanged, only output.dir moves
- figure scripts, SI figure sources, notebooks, REPRODUCING.md, README and the
SI Methods/tables updated; make clean no longer deletes tracked manifests;
reproduce.sh hashes the s{seed}/ layouts too
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
29 lines
1.2 KiB
YAML
29 lines
1.2 KiB
YAML
experiment: kernel_sharpen
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kind: lineage
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seed: 20260705
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n_replicates: 24
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# (Learning-kernel bridge, pro-collapse arm): does neutral Wright-Fisher explain the VAE's
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# collapse on MNIST? NO -- and that is the point. This matches the MNIST regime (K=30, n=6000,
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# Zipf) where drift is nearly inert: neutral (temperature=1.0) barely moves (H stays ~H*, ~all
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# modes alive), yet the real VAE collapsed to a SINGLE mode (results/fig2_mnist_collapse). Adding the
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# estimator's sharpening / mode-competition (temperature<1: p ~ p^(1/tau)) reproduces the
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# catastrophic collapse. tau=0.8 is calibrated to reproduce collapse-to-one-mode. This is the
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# axis Riis (2026) names as future work: the estimator, not the sampling, drives VAE collapse.
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truth: {K: 30, R: 1, tail: zipf, zipf_s: 1.5, tail_threshold: 0.01, init: truth}
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dynamics:
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n: 6000 # huge vs K=30 -> neutral drift is essentially inert
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grounding: {m: 0, policy: proportional}
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kernel: {reset: 0.0, temperature: 1.0, floor: 0.0}
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generations: 15
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metrics: {kl_floor: 1.0e-9, support_eps: 1.0e-9}
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sweep:
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- param: dynamics.kernel.temperature
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values: [1.0, 0.8] # neutral (no collapse) vs sharpened (catastrophic collapse)
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output: {dir: results/figS2_kernel_sharpen}
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