AI RESEARCH
DistMatch: Adaptive Binning via Distribution Matching for Robust Sequential Conformal Prediction
arXiv CS.LG
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ArXi:2606.00690v1 Announce Type: new Sequential conformal prediction (CP) provides valid uncertainty quantification under the assumption of residual exchangeability. However, this assumption is often violated in real-world time series due to temporal dependencies and distributional shifts. While recent methods attempt to approximate exchangeability through reweighting, identifying optimal weights remains an open challenge.