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Staged Depth Training (SDT), which trains a shallow prefix under a temporary physics-informed head, discards the head, and freezes the learned prefix while adding depth, supports representation curriculum as a promising training strategy for improving PINNs while preserving the deployed architecture and inference cost.
To the knowledge, AgonAlpha is the first alpha-mining system to combine verified artifact search, a fresh-context adversarial reviewer with re-execution and veto authority, and pending-aware parallel budget allocation, together with a complete public evidence trail.
This work provides an open measurement framework deployable on any model exposing block identities, and introduces a dense-calibrated counterfactual audit using matched probe cards to isolate the sparsification-specific effect.
Automatic Symbolic Regression (AutoSR), a fully automated system that instantiates Research-Space Symbolic Regression by searching persistent scientific investigations by searching persistent scientific investigations rather than isolated equations, is introduced.
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