6 papers
Interface Laplace Learning: Learnable Interface Term Helps Semi-Supervised Learning
Tangjun Wang, Chenglong Bao, Zuoqiang Shi
We introduce a novel framework, called Interface Laplace learning, for graph-based semi-supervised learning. Motivated by the observation that an interface should exist between dif…
A network based approach for unbalanced optimal transport on surfaces
Jiangong Pan, Wei Wan, Yuejin Zhang +2
In this paper, we present a neural network approach to address the dynamic unbalanced optimal transport problem on surfaces with point cloud representation. For surfaces with point…
Reconstruction of dynamical systems from data without time labels
Zhijun Zeng, Pipi Hu, Chenglong Bao +2
In this paper, we study the method to reconstruct dynamical systems from data without time labels. Data without time labels appear in many applications, such as molecular dynamics,…
A Neural Network Framework for High-Dimensional Dynamic Unbalanced Optimal Transport
Wei Wan, Jiangong Pan, Yuejin Zhang +2
In this paper, we introduce a neural network-based method to address the high-dimensional dynamic unbalanced optimal transport (UOT) problem. Dynamic UOT focuses on the optimal tra…
Fast and Globally Consistent Normal Orientation based on the Winding Number Normal Consistency
Siyou Lin, Zuoqiang Shi, Yebin Liu
Estimating consistently oriented normals for point clouds enables a number of important applications in computer graphics. While local normal estimation is possible with simple tec…
Fast and Scalable Semi-Supervised Learning for Multi-View Subspace Clustering
Huaming Ling, Chenglong Bao, Jiebo Song +1
In this paper, we introduce a Fast and Scalable Semi-supervised Multi-view Subspace Clustering (FSSMSC) method, a novel solution to the high computational complexity commonly found…