119 citations · 208 across the 7 of their papers we have counts for
4 papers · 1 filter
Curvature Regularization to Prevent Distortion in Graph Embedding
Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang +2
Recent research on graph embedding has achieved success in various applications. Most graph embedding methods preserve the proximity in a graph into a manifold in an embedding spac…
Geom-GCN: Geometric Graph Convolutional Networks
Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang +2
Message-passing neural networks (MPNNs) have been successfully applied to representation learning on graphs in a variety of real-world applications. However, two fundamental weakne…
Label Embedding Network: Learning Label Representation for Soft Training of Deep Networks
Xu Sun, Bingzhen Wei, Xuancheng Ren +1
We propose a method, called Label Embedding Network, which can learn label representation (label embedding) during the training process of deep networks. With the proposed method,…
Minimal Effort Back Propagation for Convolutional Neural Networks
Bingzhen Wei, Xu Sun, Xuancheng Ren +1
As traditional neural network consumes a significant amount of computing resources during back propagation, \citet{Sun2017mePropSB} propose a simple yet effective technique to alle…