7 citations · 17 across the 6 of their papers we have counts for
5 papers · 1 filter
SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP
Jie Chen, Shouzhen Chen, Mingyuan Bai +3
The message-passing mechanism helps Graph Neural Networks (GNNs) achieve remarkable results on various node classification tasks. Nevertheless, the recursive nodes fetching and agg…
Universal Deep GNNs: Rethinking Residual Connection in GNNs from a Path Decomposition Perspective for Preventing the Over-smoothing
Jie Chen, Weiqi Liu, Zhizhong Huang +3
The performance of GNNs degrades as they become deeper due to the over-smoothing. Among all the attempts to prevent over-smoothing, residual connection is one of the promising meth…
Neural Ordinary Differential Equation Model for Evolutionary Subspace Clustering and Its Applications
Mingyuan Bai, S. T. Boris Choy, Junping Zhang +1
The neural ordinary differential equation (neural ODE) model has attracted increasing attention in time series analysis for its capability to process irregular time steps, i.e., da…
STAS: Adaptive Selecting Spatio-Temporal Deep Features for Improving Bias Correction on Precipitation
Yiqun Liu, Shouzhen Chen, Lei Chen +4
Numerical Weather Prediction (NWP) can reduce human suffering by predicting disastrous precipitation in time. A commonly-used NWP in the world is the European Centre for medium-ran…
Towards a Precipitation Bias Corrector against Noise and Maldistribution
Xiaoyang Xu, Yiqun Liu, Hanqing Chao +5
With broad applications in various public services like aviation management and urban disaster warning, numerical precipitation prediction plays a crucial role in weather forecast.…