Part IV: Deep Learning for Sensor Time Series
Chapter 18  [A][R]

Uncertainty, Calibration, and Conformal Prediction

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Sections

  1. 18.1 Aleatoric vs epistemic uncertainty revisited
  2. 18.2 Calibration and temperature scaling for time series
  3. 18.3 Deep ensembles, MC-dropout, Bayesian and evidential DL
  4. 18.4 Conformal prediction: split, weighted, and the exchangeability problem
  5. 18.5 Adaptive conformal inference (ACI) and conformal PID under drift
  6. 18.6 Abstention, fallback, and safety margins
  7. 18.7 Reporting uncertainty to downstream systems

Lab 18

compare split conformal vs ACI on a drifting sensor stream; verify coverage and interval width.