AINeutralarXiv – CS AI · 18h ago6/10
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Instrumented data for causal scientific machine learning
Researchers propose 'instrumented data' as a new paradigm for scientific machine learning, where each data point carries its mechanistic model, uncertainty estimates, and executable counterfactuals. This approach bridges observational data and synthetic data by creating sensor-backed simulations with explicit parameters and causal intervention capabilities, with applications across computational biology, climate modeling, materials science, and medical imaging.