Proposes imCP framework that uses independent samples from the invariant measure of a Markov process for conformal calibration in one-step and multi-step predictions of learned dynamical systems.
arXiv preprint arXiv:2005.07972 , year =
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Uncertainty Quantification via Invariant-Measure Conformal Prediction
Proposes imCP framework that uses independent samples from the invariant measure of a Markov process for conformal calibration in one-step and multi-step predictions of learned dynamical systems.