E-raamat: Belief Functions: Theory and Applications: 8th International Conference, BELIEF 2024, Belfast, UK, September 2-4, 2024, Proceedings

.- Machine learning. 



.- Deep evidential clustering of images.



.- Incremental Belief-peaks Evidential Clustering.



.- Imprecise Deep Networks for Uncertain Image Classification.



.- Dempster-Shafer Credal Probabilistic Circuits.



.- Uncertainty quantification in regression neural networks using
likelihood-based belief functions.



.- An evidential time-to-event prediction model based on Gaussian random
fuzzy numbers.



.- Object Hallucination Detection in Large Vision Language Models via
Evidential Conflict.



.- Multi-oversampling with evidence fusion for imbalanced data
classification.



.- An Evidence-based Framework For Heterogeneous Electronic Health Records: A
Case Study In Mortality Prediction.



.- Conflict Management in a Distance to Prototype-Based Evidential Deep
Learning.



.- A Novel Privacy Preserving Framework for Training Dempster-Shafer
Theory-based Evidential Deep Neural Network.



.- Statistical inference. 



.- Large-sample theory for inferential models: A possibilistic Bernsteinvon
Mises theorem.



.- Variational approximations of possibilistic inferential models.



.- Decision theory via model-free generalized fiducial inference.



.- Which statistical hypotheses are afflicted with false confidence?.



.- Algebraic expression for the relative likelihood-based evidential
prediction of an ordinal variable.



.- Information fusion and optimization. 



.- Why Combining Belief Functions on Quantum Circuits?.



.- SHADED: Shapley Value-based Deceptive Evidence Detection in Belief
Functions.



.- A Novel Optimization-Based Combination Rule for Dempster-Shafer Theory.



.- Fusing independent inferential models in a black-box manner.



.- Optimization under Severe Uncertainty: a Generalized Minimax Regret
Approach for Problems with Linear Objectives.



.- Measures of uncertainty, conflict and distances. 



.- A mean distance between elements of same class for rich labels.



.- Threshold Functions and Operations in the Theory of Evidence.



.- Mutual Information and Kullback-Leibler Divergence in the Dempster-Shafer
Theory.



.- An OWA-based Distance Measure for Ordered Frames of Discernment.



.- Automated Hierarchical Conflict Reduction for Crowdsourced Annotation
Tasks using Belief Functions.



.- Continuous belief functions, logics, computation. 



.- Gamma Belief Functions.



.- Combination of Dependent Gaussian Random Fuzzy Numbers.



.- A 3-valued Logical Foundation for Evidential Reasoning.



.- Accelerated Dempster Shafer using Tensor Train Representation.