2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.AI2024
UR4NNV: Neural Network Verification, Under-approximation Reachability Works!
Zhen Liang, Taoran Wu, Ran Zhao +5
Recently, formal verification of deep neural networks (DNNs) has garnered considerable attention, and over-approximation based methods have become popular due to their effectivenes…
cs.LG2023★ 2 cited
SODA: Robust Training of Test-Time Data Adaptors
Zige Wang, Yonggang Zhang, Zhen Fang +3
Adapting models deployed to test distributions can mitigate the performance degradation caused by distribution shifts. However, privacy concerns may render model parameters inacces…
cs.LG2023★ 1 cited
Repairing Deep Neural Networks Based on Behavior Imitation
Zhen Liang, Taoran Wu, Changyuan Zhao +4
The increasing use of deep neural networks (DNNs) in safety-critical systems has raised concerns about their potential for exhibiting ill-behaviors. While DNN verification and test…