3 citations · 6 across the 5 of their papers we have counts for
5 papers · 1 filter
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…
DOS: Diverse Outlier Sampling for Out-of-Distribution Detection
Wenyu Jiang, Hao Cheng, Mingcai Chen +2
Modern neural networks are known to give overconfident prediction for out-of-distribution inputs when deployed in the open world. It is common practice to leverage a surrogate outl…
MixBoost: Improving the Robustness of Deep Neural Networks by Boosting Data Augmentation
Zhendong Liu, Wenyu Jiang, Min guo +1
As more and more artificial intelligence (AI) technologies move from the laboratory to real-world applications, the open-set and robustness challenges brought by data from the real…
Explanation-based Counterfactual Retraining(XCR): A Calibration Method for Black-box Models
Liu Zhendong, Wenyu Jiang, Yi Zhang +1
With the rapid development of eXplainable Artificial Intelligence (XAI), a long line of past work has shown concerns about the Out-of-Distribution (OOD) problem in perturbation-bas…
Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning with Label Noise
Mingcai Chen, Hao Cheng, Yuntao Du +3
Noisy labels damage the performance of deep networks. For robust learning, a prominent two-stage pipeline alternates between eliminating possible incorrect labels and semi-supervis…