25 citations · 27 across the 7 of their papers we have counts for
5 papers · 1 filter
C-Adapter: Adapting Deep Classifiers for Efficient Conformal Prediction Sets
Kangdao Liu, Hao Zeng, Jianguo Huang +3
Conformal prediction, as an emerging uncertainty quantification technique, typically functions as post-hoc processing for the outputs of trained classifiers. To optimize the classi…
Similarity-Navigated Conformal Prediction for Graph Neural Networks
Jianqing Song, Jianguo Huang, Wenyu Jiang +3
Graph Neural Networks have achieved remarkable accuracy in semi-supervised node classification tasks. However, these results lack reliable uncertainty estimates. Conformal predicti…
TorchCP: A Python Library for Conformal Prediction
Jianguo Huang, Jianqing Song, Xuanning Zhou +2
Conformal prediction (CP) is a powerful statistical framework that generates prediction intervals or sets with guaranteed coverage probability. While CP algorithms have evolved bey…
Does confidence calibration improve conformal prediction?
Huajun Xi, Jianguo Huang, Kangdao Liu +2
Conformal prediction is an emerging technique for uncertainty quantification that constructs prediction sets guaranteed to contain the true label with a predefined probability. Pre…
Resolution invariant deep operator network for PDEs with complex geometries
Jianguo Huang, Yue Qiu
Neural operators (NO) are discretization invariant deep learning methods with functional output and can approximate any continuous operator. NO have demonstrated the superiority of…