103 citations · 114 across the 11 of their papers we have counts for
4 papers · 1 filter
MTM: A Multi-Scale Token Mixing Transformer for Irregular Multivariate Time Series Classification
Shuhan Zhong, Weipeng Zhuo, Sizhe Song +3
Irregular multivariate time series (IMTS) is characterized by the lack of synchronized observations across its different channels. In this paper, we point out that this channel-wis…
M-Impute: Mask-guided Representation Learning for Missing Value Imputation
Zhongyi Yu, Zhenghao Wu, Shuhan Zhong +4
Missing values are a common problem that poses significant challenges to data analysis and machine learning. This problem necessitates the development of an effective imputation me…
SDT-GNN: Streaming-based Distributed Training Framework for Graph Neural Networks
Xin Huang, Weipeng Zhuo, Minh Phu Vuong +4
Recently, distributed GNN training frameworks, such as DistDGL and PyG, have been developed to enable training GNN models on large graphs by leveraging multiple GPUs in a distribut…
A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis
Shuhan Zhong, Sizhe Song, Weipeng Zhuo +3
Time series data, including univariate and multivariate ones, are characterized by unique composition and complex multi-scale temporal variations. They often require special consid…