11 citations · 44 across the 16 of their papers we have counts for
5 papers · 1 filter
Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao +6
It is quite challenging to ensure the safety of reinforcement learning (RL) agents in an unknown and stochastic environment under hard constraints that require the system state not…
A Tool for Neural Network Global Robustness Certification and Training
Zhilu Wang, Yixuan Wang, Feisi Fu +4
With the increment of interest in leveraging machine learning technology in safety-critical systems, the robustness of neural networks under external disturbance receives more and…
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction
Ruochen Jiao, Xiangguo Liu, Takami Sato +2
Predicting the trajectories of surrounding objects is a critical task for self-driving vehicles and many other autonomous systems. Recent works demonstrate that adversarial attacks…
TAE: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictor
Ruochen Jiao, Xiangguo Liu, Bowen Zheng +2
Trajectory generation and prediction are two interwoven tasks that play important roles in planner evaluation and decision making for intelligent vehicles. Most existing methods fo…
Safety-driven Interactive Planning for Neural Network-based Lane Changing
Xiangguo Liu, Ruochen Jiao, Bowen Zheng +2
Neural network-based driving planners have shown great promises in improving task performance of autonomous driving. However, it is critical and yet very challenging to ensure the…