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Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes

Conformal Inference is (almost) Free for Neural Networks Trained with Early Stopping

ICML 2023 · Probabilistic and scientific modeling › Uncertainty and Gaussian processes · approach: Conformal prediction methods · 2 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use CES instead of early stopping with data splittingNeural networks for CIFAR10 outlier detection · CIFAR10TPRHelped
Use CES instead of naive early stopping with the hybrid theoretical correctionNeural networks for CIFAR10 outlier detection · CIFAR10TPRHelped
Use CES instead of full training without early stoppingNeural networks for CIFAR10 outlier detection · CIFAR10TPRHelped
Use CES instead of other compared methodsNeural networks for CIFAR10 multi-class classification · CIFAR10Prediction-set cardinalityHelped
Use CES instead of early stopping with data splittingNeural networks for regression · bioAverage interval widthHelped
Use full training instead of CESNeural networks for regression · bioWorst-slab conditional coverageHurt
Use full training instead of CESNeural networks for quantile regression · homesWorst-slab conditional coverageHurt
Use CES instead of early stopping with data splittingNeural networks for quantile regression · homesWorst-slab conditional coverageHelped
Use the uncorrected naive benchmark instead of CESNeural networks for outlier detection, classification, and regression · CIFAR10 and UCI datasetsPerformanceNo clear effect

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