3 citations · 3 across the 5 of their papers we have counts for
5 papers
Achieving Universal Approximation and Universal Interpolation via Nonlinearity of Control Families
Yongqiang Cai, Yifei Duan
A significant connection exists between the controllability of dynamical systems and the approximation capabilities of neural networks, where residual networks and vanilla feedforw…
Retrieval Backward Attention without Additional Training: Enhance Embeddings of Large Language Models via Repetition
Yifei Duan, Raphael Shang, Deng Liang +1
Language models can be viewed as functions that embed text into Euclidean space, where the quality of the embedding vectors directly determines model performance, training such neu…
A Minimal Control Family of Dynamical Systems for Universal Approximation
Yifei Duan, Yongqiang Cai
The universal approximation property (UAP) holds a fundamental position in deep learning, as it provides a theoretical foundation for the expressive power of neural networks. It is…
Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation
Li'ang Li, Yifei Duan, Guanghua Ji +1
The study of universal approximation properties (UAP) for neural networks (NN) has a long history. When the network width is unlimited, only a single hidden layer is sufficient for…
Vanilla Feedforward Neural Networks as a Discretization of Dynamical Systems
Yifei Duan, Li'ang Li, Guanghua Ji +1
Deep learning has made significant applications in the field of data science and natural science. Some studies have linked deep neural networks to dynamic systems, but the network…