4 papers · 1 filter
Noise-robust Contrastive Learning for Critical Transition Detection in Dynamical Systems
Wenqi Fang, Ye Li
Detecting critical transitions in complex, noisy time-series data is a fundamental challenge across science and engineering. Such transitions may be anticipated by the emergence of…
A Fast Initialization Method for Neural Network Controllers: A Case Study of Image-based Visual Servoing Control for the multicopter Interception
Chenxu Ke, Congling Tian, Kaichen Xu +2
Reinforcement learning-based controller design methods often require substantial data in the initial training phase. Moreover, the training process tends to exhibit strong randomne…
Image Segmentation via Variational Model Based Tailored UNet: A Deep Variational Framework
Kaili Qi, Wenli Yang, Ye Li +1
Traditional image segmentation methods, such as variational models based on partial differential equations (PDEs), offer strong mathematical interpretability and precise boundary m…
Convergence analysis of wide shallow neural operators within the framework of Neural Tangent Kernel
Xianliang Xu, Ye Li, Zhongyi Huang
Neural operators are aiming at approximating operators mapping between Banach spaces of functions, achieving much success in the field of scientific computing. Compared to certain…