91 citations · 114 across the 8 of their papers we have counts for
8 papers
Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous Driving
Wei-Xin Li, Xiaodong Yang
Evaluating the performance of perception modules in autonomous driving is one of the most critical tasks in developing the complex intelligent system. While module-level unit test…
ProphNet: Efficient Agent-Centric Motion Forecasting with Anchor-Informed Proposals
Xishun Wang, Tong Su, Fang Da +1
Motion forecasting is a key module in an autonomous driving system. Due to the heterogeneous nature of multi-sourced input, multimodality in agent behavior, and low latency require…
Neural Network Repair with Reachability Analysis
Xiaodong Yang, Tom Yamaguchi, Hoang-Dung Tran +3
Safety is a critical concern for the next generation of autonomy that is likely to rely heavily on deep neural networks for perception and control. Formally verifying the safety an…
Reachability Analysis of Convolutional Neural Networks
Xiaodong Yang, Tomoya Yamaguchi, Hoang-Dung Tran +3
Deep convolutional neural networks have been widely employed as an effective technique to handle complex and practical problems. However, one of the fundamental problems is the lac…
Reachable Set Estimation for Neural Network Control Systems: A Simulation-Guided Approach
Weiming Xiang, Hoang-Dung Tran, Xiaodong Yang +1
The vulnerability of artificial intelligence (AI) and machine learning (ML) against adversarial disturbances and attacks significantly restricts their applicability in safety-criti…
NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems
Hoang-Dung Tran, Xiaodong Yang, Diego Manzanas Lopez +5
This paper presents the Neural Network Verification (NNV) software tool, a set-based verification framework for deep neural networks (DNNs) and learning-enabled cyber-physical syst…
Reachability Analysis for Feed-Forward Neural Networks using Face Lattices
Xiaodong Yang, Hoang-Dung Tran, Weiming Xiang +1
The paper introduces a parallelizable method that uses face lattices to compute exact reachable sets for feed‑forward ReLU neural networks, enabling more efficient safety verificat…
Verification for Machine Learning, Autonomy, and Neural Networks Survey
Weiming Xiang, Patrick Musau, Ayana A. Wild +5
This survey presents an overview of verification techniques for autonomous systems, with a focus on safety-critical autonomous cyber-physical systems (CPS) and subcomponents thereo…