31 citations · 32 across the 4 of their papers we have counts for
4 papers
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…
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…
PGformer: Proxy-Bridged Game Transformer for Multi-Person Highly Interactive Extreme Motion Prediction
Yanwen Fang, Jintai Chen, Peng-Tao Jiang +4
Multi-person motion prediction is a challenging task, especially for real-world scenarios of highly interacted persons. Most previous works have been devoted to studying the case o…
Hypergraph Transformer for Skeleton-based Action Recognition
Yuxuan Zhou, Zhi-Qi Cheng, Chao Li +4
Skeleton-based action recognition aims to recognize human actions given human joint coordinates with skeletal interconnections. By defining a graph with joints as vertices and thei…