First application of split conformal prediction to neural operators, providing distribution-free intervals with 89.1% empirical coverage on heat conduction benchmarks and an adaptive normalized variant using MC Dropout.
Estimating the uncertainty of neural network predictions using conformal prediction
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Conformal Prediction for Neural Operators: Distribution-Free Uncertainty Quantification in Physics Simulation
First application of split conformal prediction to neural operators, providing distribution-free intervals with 89.1% empirical coverage on heat conduction benchmarks and an adaptive normalized variant using MC Dropout.