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Counterfactual Predictions in Scientific Emulators Without Controlled Experiments

arXiv cs.LG ↗ · 2026-10-05 Cached

The paper introduces ReRoute, a framework for counterfactual 'what-if' prediction in scientific emulators that combines factual data with partial mechanistic knowledge—without needing controlled intervention data—achieving 18.2–31.8% lower climate error under CO2 distribution shifts. Its causal identification result is machine-checked in Lean, with applications to advection–diffusion systems, coupled-climate emulation, and ERA5-trained emulators.

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