3 citations · 3 across the 3 of their papers we have counts for
5 papers
Synthesizing Probabilistic Saturating Counters with Differentially Private Formal Guarantees
Zhiming Chi, Lutan Zhao, Depeng Liu +8
Branch predictors improve instruction-level parallelism in modern processors and are commonly modeled using saturating counters. However, classical saturating counters are determin…
TrajRS: Towards Certified Robustness in Pedestrian Trajectory Prediction
Liang Zhang, Gaojie Jin, Yao Shi +4
The robustness of trajectory prediction models is crucial for developing safe autonomous driving systems. Adversarial attacks on trajectory prediction can significantly impair the…
Safety Analysis of Autonomous Driving Systems Based on Model Learning
Renjue Li, Tianhang Qin, Pengfei Yang +3
We present a practical verification method for safety analysis of the autonomous driving system (ADS). The main idea is to build a surrogate model that quantitatively depicts the b…
Ensemble Defense with Data Diversity: Weak Correlation Implies Strong Robustness
Renjue Li, Hanwei Zhang, Pengfei Yang +4
In this paper, we propose a framework of filter-based ensemble of deep neuralnetworks (DNNs) to defend against adversarial attacks. The framework builds an ensemble of sub-models -…
Improving Neural Network Verification through Spurious Region Guided Refinement
Pengfei Yang, Renjue Li, Jianlin Li +5
We propose a spurious region guided refinement approach for robustness verification of deep neural networks. Our method starts with applying the DeepPoly abstract domain to analyze…