8 citations · 19 across the 12 of their papers we have counts for
4 papers · 1 filter
DeLELSTM: Decomposition-based Linear Explainable LSTM to Capture Instantaneous and Long-term Effects in Time Series
Chaoqun Wang, Yijun Li, Xiangqian Sun +3
Time series forecasting is prevalent in various real-world applications. Despite the promising results of deep learning models in time series forecasting, especially the Recurrent…
Probabilistic Learning of Multivariate Time Series with Temporal Irregularity
Yijun Li, Cheuk Hang Leung, Qi Wu
Probabilistic forecasting of multivariate time series is essential for various downstream tasks. Most existing approaches rely on the sequences being uniformly spaced and aligned a…
Deep into The Domain Shift: Transfer Learning through Dependence Regularization
Shumin Ma, Zhiri Yuan, Qi Wu +5
Classical Domain Adaptation methods acquire transferability by regularizing the overall distributional discrepancies between features in the source domain (labeled) and features in…
Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Information
Yiyan Huang, Cheuk Hang Leung, Shumin Ma +3
Estimating the average treatment effect (ATE) from observational data is challenging due to selection bias. Existing works mainly tackle this challenge in two ways. Some researcher…