Titlebook: Belief Functions: Theory and Applications; 8th International Co Yaxin Bi,Anne-Laure Jousselme,Thierry Denoeux Conference proceedings 2024 T

合适

An Evidential Time-to-Event Prediction Model Based on Gaussian Random Fuzzy Numbersandom fuzzy numbers, a newly introduced family of random fuzzy subsets of the real line with associated belief functions, generalizing both Gaussian random variables and Gaussian possibility distributions. Our approach makes minimal assumptions about the underlying time-to-event distribution. The mo

refraction

Object Hallucination Detection in Large Vision Language Models via Evidential Conflict. This is particularly presented as the object hallucination, where the models inaccurately describe objects in the images. Current efforts mainly focus on detecting such erroneous behaviors through the semantic consistency of outputs via multiple inferences or by evaluating the entropy-based uncert

EVADE

Multi-oversampling with Evidence Fusion for Imbalanced Data Classificationt oversampling methods overlook the uncertainty in the samples produced, potentially shifting the data’s distribution and adversely affecting the classification outcomes. To address this problem, we introduce a multi-oversampling with evidence fusion (MOEF) method for imbalanced data classification

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legacy

Conflict Management in a Distance to Prototype-Based Evidential Deep Learningent of perception models. If the pieces of evidence involved in the merging process of the deep learning-based model are discordant, the results can be degraded. Therefore, verifying the conflicting level of sources and alleviating it when possible, gives the capability to increase efficiency of fol

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ARK

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Variational Approximations of Possibilistic Inferential Modelsient computation in applications is a major challenge. This paper presents a simple and apparently powerful Monte Carlo-driven strategy for approximating the IM’s possibility contour, or at least its .-level set for a specified .. Our proposal utilizes a parametric family that, in a certain sense, a

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Which Statistical Hypotheses are Afflicted with False Confidence?ivial and non-trivial) false hypotheses to which the method tends to assign high confidence. This raises concerns about the reliability of these widely-used methods, and shines promising light on the consonant belief function-based methods that are provably immune to false confidence. But an existen