2 papers
cs.LG2026
Learning Reduced-Order Dynamics with Singularity via Latent-Augmented Neural Ordinary Differential Equations
Xiaorui Wang, Yu Zhou, Wenjie Mei +3
This paper addresses the issue of self-intersecting trajectories (in phase space) in industrial reduced-order modeling and proposes the Latent-Augmented Neural Ordinary Differentia…
math.OC2026
Finite-Time Optimization via Scaled Gradient-Momentum Flows
Yu Zhou, Mengmou Li, Masaaki Nagahara
In this paper, we develop a scaled gradient-momentum framework for continuous-time optimization that achieves global finite-time convergence. A state-dependent scaling mechanism is…