Paper Accepted by HSCC 2026

Our paper has been accepted for presentation at HSCC 2026.

Our paper titled “Derivative-Agnostic Inference of Nonlinear Hybrid Systems” by Hengzhi Yu, Bohan Ma, Mingshuai Chen, Huangying Dong, Jie An (ISCAS), Bin Gu (Beijing Institute of Control Engineering), Naijun Zhan (PKU), and Jianwei Yin has been accepted by HSCC 2026 – The 29th ACM International Conference on Hybrid Systems: Computation and Control at Saint Malo, France. This paper presents Dainarx – a derivative-agnostic approach to inferring nonlinear hybrid automata whose dynamics are captured by nonlinear autoregressive exogenous (NARX) models. Dainarx is, to the best of our knowledge, the first approach that admits high-order non-polynomial dynamics with non-polynomial inputs/guards, and linear resets.