ProbRes is a post-hoc calibration technique that models conditional volatility separately from the mean and uses residual resampling to generate well-calibrated predictive distributions for univariate and multivariate time series.
Recurrent interpolants for probabilistic time series prediction
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ProbRes: Volatility Learning for Probabilistic Time-Series Forecasting
ProbRes is a post-hoc calibration technique that models conditional volatility separately from the mean and uses residual resampling to generate well-calibrated predictive distributions for univariate and multivariate time series.