1k citations · 1.4k across the 22 of their papers we have counts for
22 papers
Multi-Agent Vulnerability Discovery for Autonomous Driving with Hazard Arbitration Reward
Weilin Liu, Ye Mu, Chao Yu +6
Discovering hazardous scenarios is crucial in testing and further improving driving policies. However, conducting efficient driving policy testing faces two key challenges. On the…
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
Yi Cai, Xuefei Ning, Huazhong Yang +1
Adversarial attacks have rendered high security risks on modern deep learning systems. Adversarial training can significantly enhance the robustness of neural network models by sup…
Enabling Lower-Power Charge-Domain Nonvolatile In-Memory Computing with Ferroelectric FETs
Guodong Yin, Yi Cai, Juejian Wu +6
Compute-in-memory (CiM) is a promising approach to alleviating the memory wall problem for domain-specific applications. Compared to current-domain CiM solutions, charge-domain CiM…
Discovering Robust Convolutional Architecture at Targeted Capacity: A Multi-Shot Approach
Xuefei Ning, Junbo Zhao, Wenshuo Li +4
Convolutional neural networks (CNNs) are vulnerable to adversarial examples, and studies show that increasing the model capacity of an architecture topology (e.g., width expansion)…
aw_nas: A Modularized and Extensible NAS framework
Xuefei Ning, Changcheng Tang, Wenshuo Li +7
Neural Architecture Search (NAS) has received extensive attention due to its capability to discover neural network architectures in an automated manner. aw_nas is an open-source Py…
Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic Scenes
Feng Gao, Jincheng Yu, Hao Shen +2
Learning depth and ego-motion from unlabeled videos via self-supervision from epipolar projection can improve the robustness and accuracy of the 3D perception and localization of v…