A survey on uncertainty reasoning and quantification in belief theory and its application to deep learning

• Published in: Information fusion Vol. 101; p. 101987
• Main Authors: Guo, Zhen, Wan, Zelin, Zhang, Qisheng, Zhao, Xujiang, Zhang, Qi, Kaplan, Lance M., Jøsang, Audun, Jeong, Dong H., Chen, Feng, Cho, Jin-Hee
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2024
• Subjects: Belief theory; Decision making; Machine/deep learning; Uncertainty quantification; Uncertainty reasoning; Uncertainty quantification; Machine/deep learning; Decision making; Uncertainty reasoning; Belief theory

An in-depth understanding of uncertainty is the first step to making effective decisions under uncertainty. Machine/deep learning (ML/DL) has been hugely leveraged to solve complex problems involved with processing high-dimensional data. However, reasoning and quantifying different uncertainties to...