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…
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…
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…
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…