A domain-validity rubric and MR-card format screen candidate metamorphic relations into auditable test assets for SciML surrogates, separating model violations from out-of-domain applications.
Kusner, Stanislas Pamela, and Marc Peter Deisenroth
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Hybrid neural world models train one network with horizon conditioning to predict multi-horizon physical states and extract a per-trajectory error map from forward passes alone for hybrid accuracy-speed operation across PDE and rigid-body domains.
citing papers explorer
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Domain-Validity-Gated Metamorphic Testing of Scientific ML Surrogates
A domain-validity rubric and MR-card format screen candidate metamorphic relations into auditable test assets for SciML surrogates, separating model violations from out-of-domain applications.
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Hybrid Neural World Models
Hybrid neural world models train one network with horizon conditioning to predict multi-horizon physical states and extract a per-trajectory error map from forward passes alone for hybrid accuracy-speed operation across PDE and rigid-body domains.