Zheyang Shen, Jeremias Knoblauch, Sam Power, and Chris Oates propose 'Prediction-Centric Uncertainty Quantification,' a method where a mixture distribution based on a deterministic model provides improved uncertainty quantification in predictive contexts, addressing the issue where misspecified deterministic models lead to incorrect, overly certain posterior predictions.

Authors

• Person: Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche Organization: AISTATS
  Track: Poster Session 3 - aistats 2026

Sources

• Track: Poster Session 3 - aistats 2026 virtual.aistats.org Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche · AISTATS via serper

Referenced by nodes (1)

• Uncertainty quantification concept