3 papers
cs.LG2025
From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics
Qinshuo Liu, Weiqin Zhao, Wei Huang +3
The depth of neural networks is a critical factor for their capability, with deeper models often demonstrating superior performance. Motivated by this, significant efforts have bee…
stat.ML2024
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
Qinshuo Liu, Zixin Wang, Xi-An Li +4
Semiparametric statistics play a pivotal role in a wide range of domains, including but not limited to missing data, causal inference, and transfer learning, to name a few. In many…
cs.LG2024
DGCformer: Deep Graph Clustering Transformer for Multivariate Time Series Forecasting
Qinshuo Liu, Yanwen Fang, Pengtao Jiang +1
Multivariate time series forecasting tasks are usually conducted in a channel-dependent (CD) way since it can incorporate more variable-relevant information. However, it may also i…