5 papers
Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial
Haoyu Li, Xiangru Zhong, Hao Cheng +2
Learning-based methods for synthesizing controllers have gained popularity due to their high expressiveness and strong empirical performance. However, in safety-critical scenarios…
Two-Stage Learning of Stabilizing Neural Controllers via Zubov Sampling and Iterative Domain Expansion
Haoyu Li, Xiangru Zhong, Bin Hu +1
Learning-based neural network (NN) control policies have shown impressive empirical performance. However, obtaining stability guarantees and estimates of the region of attraction o…
Safe Domains of Attraction for Discrete-Time Nonlinear Systems: Characterization and Verifiable Neural Network Estimation
Mohamed Serry, Haoyu Li, Ruikun Zhou +2
Analysis of nonlinear autonomous systems typically involves estimating domains of attraction, which have been a topic of extensive research interest for decades. Despite that, accu…
Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems
Haoyu Li, Xiangru Zhong, Bin Hu +1
Contraction metrics are crucial in control theory because they provide a powerful framework for analyzing stability, robustness, and convergence of various dynamical systems. Howev…
Abstract Rendering: Computing All that is Seen in Gaussian Splat Scenes
Yangge Li, Chenxi Ji, Xiangru Zhong +2
We introduce abstract rendering, a method for computing a set of images by rendering a scene from a continuously varying range of camera positions. The resulting abstract image-whi…