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Survey details statistical inference with belief functions

A new survey paper details statistical inference methods using belief functions, a framework for characterizing uncertainty when probability distributions are impractical due to limited data. The paper specifically reviews significant contributions to learning belief measures from statistical data, offering a comprehensive overview of the field. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Provides a foundational overview of uncertainty quantification methods relevant to AI systems.

RANK_REASON The cluster contains a survey paper on a statistical method. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 · Fabio Cuzzolin ·

    Statistical inference with belief functions: A survey

    Belief functions are a powerful and popular framework for the mathematical characterisation of uncertainty, in particular in situations in which lack of data renders learning a probability distribution for the problem impractical. The first step in a reasoning chain based on beli…