deep neural networks 1evidential deep learning 1out-of-distribution detection 1uncertainty quantification 1variational inference 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Variational Inference for Evidential Deep Learning
Jiawei Tang, Xinyan Du, Hui Liu +2
The paper introduces VI-EDL, a variational inference framework for evidential deep learning that controls evidence growth and provides theoretical guarantees for uncertainty estima…
cs.LG2025
Towards Better IncomLDL: We Are Unaware of Hidden Labels in Advance
Jiecheng Jiang, Jiawei Tang, Jiahao Jiang +3
Label distribution learning (LDL) is a novel paradigm that describe the samples by label distribution of a sample. However, acquiring LDL dataset is costly and time-consuming, whic…
cs.LG2025
Concentration Distribution Learning from Label Distributions
Jiawei Tang, Yuheng Jia
Label distribution learning (LDL) is an effective method to predict the relative label description degree (a.k.a. label distribution) of a sample. However, the label distribution i…