A verification-first agentic workflow for SciML surrogate discovery adds per-candidate, machine-checkable physics audits that expose a causality failure an error-only baseline misses.
A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials.Computer Methods in Applied Mechanics and Engineering, 391, 2022
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Physics-Audited Agentic Discovery in Scientific Machine Learning
A verification-first agentic workflow for SciML surrogate discovery adds per-candidate, machine-checkable physics audits that expose a causality failure an error-only baseline misses.