1 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
AutoSGNN: Automatic Propagation Mechanism Discovery for Spectral Graph Neural Networks
Shibing Mo, Kai Wu, Qixuan Gao +2
In real-world applications, spectral Graph Neural Networks (GNNs) are powerful tools for processing diverse types of graphs. However, a single GNN often struggles to handle differe…
Automated Loss function Search for Class-imbalanced Node Classification
Xinyu Guo, Kai Wu, Xiaoyu Zhang +1
Class-imbalanced node classification tasks are prevalent in real-world scenarios. Due to the uneven distribution of nodes across different classes, learning high-quality node repre…
Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-time Dynamics
Lanlan Chen, Kai Wu, Jian Lou +1
Modeling continuous-time dynamics constitutes a foundational challenge, and uncovering inter-component correlations within complex systems holds promise for enhancing the efficacy…
B2Opt: Learning to Optimize Black-box Optimization with Little Budget
Xiaobin Li, Kai Wu, Xiaoyu Zhang +2
The core challenge of high-dimensional and expensive black-box optimization (BBO) is how to obtain better performance faster with little function evaluation cost. The essence of th…