Verification of Probabilistic Predictions: A Brief Review

By A. H. Murphy, E. S. Epstein. 1967

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Arthur Zimek
2. Erich Schubert
3. Hans-Peter Kriegel
4. Peer Kröger
5. Charu C. Aggarwal
6. Tilmann Gneiting
7. Dustin Tran
8. Michael W. Dusenberry

Citations in the corpus

• Measuring Calibration in Deep Learning (2019, background): “One mathematical formulation of the reliability of confidence is calibration (Murphy and Epstein, 1967; Dawid, 1982).”
• Interpreting and Unifying Outlier Scores (2011, background): “in [37], for different classical evaluation measures see [36]) is not directly applicable to the scenario of outlier probability estimates.”
• Scoring Rules for Continuous Probability Distributions (1976, background): “, Sanders [13], Murphy and Epstein [11], Murphy [9], [10]), it appears that partitioning of the function representing the expected score has not been considered.”
• The Well-Calibrated Bayesian (1982, background): “Probability forecasts can be judged by several criteria (Murphy and Epstein 1967).”