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cs.LG2024
Revisiting Essential and Nonessential Settings of Evidential Deep Learning
Mengyuan Chen, Junyu Gao, Changsheng Xu
Evidential Deep Learning (EDL) is an emerging method for uncertainty estimation that provides reliable predictive uncertainty in a single forward pass, attracting significant atten…
cs.LG2024
A Comprehensive Survey on Evidential Deep Learning and Its Applications
Junyu Gao, Mengyuan Chen, Liangyu Xiang +1
Reliable uncertainty estimation has become a crucial requirement for the industrial deployment of deep learning algorithms, particularly in high-risk applications such as autonomou…
cs.LG2023
Learning Transferable Conceptual Prototypes for Interpretable Unsupervised Domain Adaptation
Junyu Gao, Xinhong Ma, Changsheng Xu
Despite the great progress of unsupervised domain adaptation (UDA) with the deep neural networks, current UDA models are opaque and cannot provide promising explanations, limiting…