14 citations · 41 across the 6 of their papers we have counts for
6 papers
Auto-resolving the atomic structure at van der Waals interfaces using a generative model
Wenqiang Huang, Yuchen Jin, Zhemin Li +12
The high-resolution visualization of atomic structures is significant for understanding the relationship between the microscopic configurations and macroscopic properties of materi…
Regularize implicit neural representation by itself
Zhemin Li, Hongxia Wang, Deyu Meng
This paper proposes a regularizer called Implicit Neural Representation Regularizer (INRR) to improve the generalization ability of the Implicit Neural Representation (INR). The IN…
Low-Rank Tensor Function Representation for Multi-Dimensional Data Recovery
Yisi Luo, Xile Zhao, Zhemin Li +2
Since higher-order tensors are naturally suitable for representing multi-dimensional data in real-world, e.g., color images and videos, low-rank tensor representation has become on…
Adaptive and Implicit Regularization for Matrix Completion
Zhemin Li, Tao Sun, Hongxia Wang +1
The explicit low-rank regularization, e.g., nuclear norm regularization, has been widely used in imaging sciences. However, it has been found that implicit regularization outperfor…
AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix Completion
Zhemin Li, Tao Sun, Hongxia Wang +1
The explicit low-rank regularization, e.g., nuclear norm regularization, has been widely used in imaging sciences. However, it has been found that implicit regularization outperfor…
A regularized deep matrix factorized model of matrix completion for image restoration
Zhemin Li, Zhi-Qin John Xu, Tao Luo +1
It has been an important approach of using matrix completion to perform image restoration. Most previous works on matrix completion focus on the low-rank property by imposing expli…