2 citations · 4 across the 5 of their papers we have counts for
5 papers
EdgeConvFormer: Dynamic Graph CNN and Transformer based Anomaly Detection in Multivariate Time Series
Jie Liu, Qilin Li, Senjian An +2
Transformer-based models for anomaly detection in multivariate time series can benefit from the self-attention mechanism due to its advantage in modeling long-term dependencies. Ho…
A Novel Exploration of Diffusion Process based on Multi-types Galton-Watson Forests
Yanjiao Zhu, Qilin Li, Wanquan Liu +2
Diffusion is a commonly used technique for spreading information from point to point on a graph. The rationale behind diffusion is not clear. And the multi-types Galton-Watson fore…
Regularizing Semi-supervised Graph Convolutional Networks with a Manifold Smoothness Loss
Qilin Li, Wanquan Liu, Ling Li
Existing graph convolutional networks focus on the neighborhood aggregation scheme. When applied to semi-supervised learning, they often suffer from the overfitting problem as the…
Semi-supervised Learning on Graph with an Alternating Diffusion Process
Qilin Li, Senjian An, Ling Li +1
Graph-based semi-supervised learning usually involves two separate stages, constructing an affinity graph and then propagating labels for transductive inference on the graph. It is…
Sparse Subspace Clustering via Diffusion Process
Qilin Li, Ling Li, Wanquan Liu
Subspace clustering refers to the problem of clustering high-dimensional data that lie in a union of low-dimensional subspaces. State-of-the-art subspace clustering methods are bas…