Enhanced Transfer Learning for Autonomous Driving with Systematic Accident Simulation. - Shivam Akhauri; Laura Y. Zheng; Ming C. Lin (IROS, 2020)

Gradient-Free Adversarial Training Against Image Corruption for Learning-based Steering. - Yu Shen; Laura Y. Zheng; Manli Shu; Weizi Li; Tom Goldstein; Ming C. Lin (NeurIPS, 2021)

Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images. - Yu Shen; Laura Y. Zheng; Manli Shu; Weizi Li; Tom Goldstein; Ming C. Lin (CoRR, 2021)

Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving. - Shivam Akhauri; Laura Y. Zheng; Tom Goldstein; Ming C. Lin (CoRR, 2021)

Traffic-Aware Autonomous Driving with Differentiable Traffic Simulation. - Laura Y. Zheng; Sanghyun Son 003; Ming C. Lin (ICRA, 2023)

Gradient Informed Proximal Policy Optimization. - Sanghyun Son 003; Laura Yu Zheng; Ryan Sullivan; Yi-Ling Qiao; Ming C. Lin (NeurIPS, 2023)

Towards Driving Policies with Personality: Modeling Behavior and Style in Risky Scenarios via Data Collection in Virtual Reality. - Laura Y. Zheng; Julio Poveda; James Mullen; Shreelekha Revankar; Ming C. Lin (CoRR, 2023)

Sensitivity-Informed Augmentation for Robust Segmentation. - Laura Y. Zheng; Wenjie Wei; Tony Wu; Jacob Clements; Shreelekha Revankar; Andre Harrison; Yu Shen; Ming C. Lin (CoRR, 2024)

Deep Stochastic Kinematic Models for Probabilistic Motion Forecasting in Traffic. - Laura Yu Zheng; Sanghyun Son 003; Jing Liang 006; Xijun Wang 002; Brian Clipp; Ming C. Lin (CoRR, 2024)