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8th BELIEF 2024: Belfast, UK
- Yaxin Bi, Anne-Laure Jousselme, Thierry Denoeux:

Belief Functions: Theory and Applications - 8th International Conference, BELIEF 2024, Belfast, UK, September 2-4, 2024, Proceedings. Lecture Notes in Computer Science 14909, Springer 2024, ISBN 978-3-031-67976-6
Machine Learning
- Loïc Guiziou, Emmanuel Ramasso, Sébastien Thibaud, Sébastien Denneulin:

Deep Evidential Clustering of Images. 3-12 - Chaoyu Gong, Sihan Wang, Zhi-gang Su:

Incremental Belief-Peaks Evidential Clustering. 13-21 - Chuanqi Liu

, Zuowei Zhang
, Zechao Liu
, Liangbo Ning
, Zhunga Liu
:
Imprecise Deep Networks for Uncertain Image Classification. 22-30 - David Ricardo Montalvan Hernandez

, Thomas Krak
, Cassio de Campos
:
Dempster-Shafer Credal Probabilistic Circuits. 31-39 - Thierry Denoeux

:
Uncertainty Quantification in Regression Neural Networks Using Likelihood-Based Belief Functions. 40-48 - Ling Huang

, Yucheng Xing, Thierry Denoeux
, Mengling Feng
:
An Evidential Time-to-Event Prediction Model Based on Gaussian Random Fuzzy Numbers. 49-57 - Zhekun Liu

, Tao Huang, Rui Wang
, Liping Jing
:
Object Hallucination Detection in Large Vision Language Models via Evidential Conflict. 58-67 - Hongpeng Tian, Zuowei Zhang, Zhunga Liu, Jingwei Zuo:

Multi-oversampling with Evidence Fusion for Imbalanced Data Classification. 68-77 - Yucheng Ruan

, Ling Huang
, Qianyi Xu
, Mengling Feng
:
An Evidence-Based Framework For Heterogeneous Electronic Health Records: A Case Study In Mortality Prediction. 78-86 - Mihreteab Negash Geletu

, Danut-Vasile Giurgi
, Thomas Josso-Laurain
, Maxime Devanne
, Jean-Philippe Lauffenburger
, Jean Dezert
:
Conflict Management in a Distance to Prototype-Based Evidential Deep Learning. 87-97 - Anh-Tu Tran, Van-Nam Huynh, Viet-Hung Dang:

A Novel Privacy Preserving Framework for Training Dempster-Shafer Theory-Based Evidential Deep Neural Network. 98-107
Statistical Inference
- Ryan Martin, Jonathan P. Williams:

Large-Sample Theory for Inferential Models: A Possibilistic Bernstein-von Mises Theorem. 111-120 - Leonardo Cella, Ryan Martin:

Variational Approximations of Possibilistic Inferential Models. 121-130 - Jonathan P. Williams, Yang Liu:

Decision Theory via Model-Free Generalized Fiducial Inference. 131-139 - Ryan Martin:

Which Statistical Hypotheses are Afflicted with False Confidence? 140-149 - Frédéric Pichon, Sébastien Ramel:

Algebraic Expression for the Relative Likelihood-Based Evidential Prediction of an Ordinal Variable. 150-158
Information Fusion and Optimization
- Qianli Zhou, Hao Luo, Éloi Bossé, Yong Deng:

Why Combining Belief Functions on Quantum Circuits? 161-170 - Haifei Zhang

:
SHADED: Shapley Value-Based Deceptive Evidence Detection in Belief Functions. 171-179 - Hasan Ihsan Turhan, Tugba Tanaydin:

A Novel Optimization-Based Combination Rule for Dempster-Shafer Theory. 180-188 - Leonardo Cella:

Fusing Independent Inferential Models in a Black-Box Manner. 189-196 - Tuan-Anh Vu

, Sohaib Afifi
, Eric Lefèvre, Frédéric Pichon:
Optimization Under Severe Uncertainty: a Generalized Minimax Regret Approach for Problems with Linear Objectives. 197-204
Measures of Uncertainty, Conflict and Distances
- Arthur Hoarau, Constance Thierry, Jean-Christophe Dubois, Yolande Le Gall:

A Mean Distance Between Elements of Same Class for Rich Labels. 207-215 - Alexander Lepskiy

:
Threshold Functions and Operations in the Theory of Evidence. 216-224 - Prakash P. Shenoy

:
Mutual Information and Kullback-Leibler Divergence in the Dempster-Shafer Theory. 225-233 - Xiong Zhao, Liyao Ma, Yiyang Wang, Shuhui Bi:

An OWA-Based Distance Measure for Ordered Frames of Discernment. 234-243 - Constance Thierry, David Gross-Amblard, Yolande Le Gall, Jean-Christophe Dubois:

Automated Hierarchical Conflict Reduction for Crowdsourced Annotation Tasks Using Belief Functions. 244-252
Continuous Belief Functions, Logics, Computation
- Liping Liu:

Gamma Belief Functions. 255-263 - Thierry Denoeux

:
Combination of Dependent Gaussian Random Fuzzy Numbers. 264-272 - Chunlai Zhou

:
A 3-Valued Logical Foundation for Evidential Reasoning. 273-282 - Duc P. Truong

, Erik Skau
, Cassandra Armstrong
, Kari Sentz
:
Accelerated Dempster Shafer Using Tensor Train Representation. 283-292

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