3 citations · 8 across the 8 of their papers we have counts for
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cs.LG2022★ 2 cited
Less Emphasis on Difficult Layer Regions: Curriculum Learning for Singularly Perturbed Convection-Diffusion-Reaction Problems
Yufeng Wang, Cong Xu, Min Yang +1
Although Physics-Informed Neural Networks (PINNs) have been successfully applied in a wide variety of science and engineering fields, they can fail to accurately predict the underl…
cs.LG2021
Missingness Augmentation: A General Approach for Improving Generative Imputation Models
Yufeng Wang, Dan Li, Cong Xu +1
Missing data imputation is a fundamental problem in data analysis, and many studies have been conducted to improve its performance by exploring model structures and learning proced…
cs.LG2020★ 3 cited
Improve Adversarial Robustness via Weight Penalization on Classification Layer
Cong Xu, Dan Li, Min Yang
It is well-known that deep neural networks are vulnerable to adversarial attacks. Recent studies show that well-designed classification parts can lead to better robustness. However…