1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
Deep Monte Carlo Quantile Regression for Quantifying Aleatoric Uncertainty in Physics-informed Temperature Field Reconstruction
Xiaohu Zheng, Wen Yao, Zhiqiang Gong +3
For the temperature field reconstruction (TFR), a complex image-to-image regression problem, the convolutional neural network (CNN) is a powerful surrogate model due to the convolu…
cs.LG2021★ 1 cited
RBUE: A ReLU-Based Uncertainty Estimation Method of Deep Neural Networks
Yufeng Xia, Jun Zhang, Zhiqiang Gong +2
Deep neural networks (DNNs) have successfully learned useful data representations in various tasks. However, assessing the reliability of these representations remains a challenge.…