Conformal Prediction for Molecular Properties under Label Shift
This work addresses one of the most pervasive obstacles to applying AI in real-world drug development by addressing conformal prediction framework tailored to label shift by weighting conformal scores using marginal label probability ratios and enhancing the trustworthiness of AI-driven predictions.
Hyeonsu Lee, Juyeong Kim, Erkhembayar Jadamba et al.
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