activity
20172025
most citedMetric Learning for Adversarial Robustness

58 citations · 62 across the 4 of their papers we have counts for

collaborators

9 papers

cs.LG2025

Dynamic Classification: Leveraging Self-Supervised Classification to Enhance Prediction Performance

Ziyuan Zhong, Junyang Zhou

In this study, we propose an innovative dynamic classification algorithm aimed at achieving zero missed detections and minimal false positives,acritical in safety-critical domains…

cs.RO20224 cited

Guided Conditional Diffusion for Controllable Traffic Simulation

Ziyuan Zhong, Davis Rempe, Danfei Xu +5

Controllable and realistic traffic simulation is critical for developing and verifying autonomous vehicles. Typical heuristic-based traffic models offer flexible control to make ve…

cs.LG2022

Repairing Group-Level Errors for DNNs Using Weighted Regularization

Ziyuan Zhong, Yuchi Tian, Conor J. Sweeney +2

Deep Neural Networks (DNNs) have been widely used in software making decisions impacting people's lives. However, they have been found to exhibit severe erroneous behaviors that ma…

cs.SE2020

Understanding Local Robustness of Deep Neural Networks under Natural Variations

Ziyuan Zhong, Yuchi Tian, Baishakhi Ray

Deep Neural Networks (DNNs) are being deployed in a wide range of settings today, from safety-critical applications like autonomous driving to commercial applications involving ima…

cs.LG201958 cited

Metric Learning for Adversarial Robustness

Chengzhi Mao, Ziyuan Zhong, Junfeng Yang +2

Deep networks are well-known to be fragile to adversarial attacks. We conduct an empirical analysis of deep representations under the state-of-the-art attack method called PGD, and…

cs.SE2019

Testing DNN Image Classifiers for Confusion & Bias Errors

Yuchi Tian, Ziyuan Zhong, Vicente Ordonez +2

Image classifiers are an important component of today's software, from consumer and business applications to safety-critical domains. The advent of Deep Neural Networks (DNNs) is t…