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Joint ARD reproduction (ICML 2026 paper #42)
Independent, rerunnable reproduction for:
- Paper: Joint Model and Data Sparsification via the Marginal Likelihood
- arXiv: 2605.29908
- OpenReview: vMcu1h3fOV
- Official repository snapshot:
58908b880b1367dd417b34160b8e324c54b44e42
The official repository contained only a README and LICENSE when audited, so this workspace implements the equations from Sections 3 and Appendices B-C directly. It does not claim to be the authors' code.
Run
uv sync --dev
uv run pytest -q
uv run python scripts/audit_claims.py
uv run python scripts/run_experiments.py --experiment both --seeds 0 1 2
All empirical outputs are explicitly labeled scaled/independent. The paper does not disclose every experiment hyperparameter (notably the RBF lengthscale), so exact Table 3/Figure 4 numerical replication is not claimed.
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