Tyler Derr

Signed Graph Convolutional Network

2018 · arXiv (Cornell University)

Due to the fact much of today's data can be represented as graphs, there has been a demand for generalizing neural network models for graph data. One recent direction that has shown fruitful results, and …

Node Similarity Preserving Graph Convolutional Networks

2020 · arXiv (Cornell University)

Graph Neural Networks (GNNs) have achieved tremendous success in various real-world applications due to their strong ability in graph representation learning. GNNs explore the graph structure and node features by aggregating and transforming information within …

Signed Graph Convolutional Networks

2018

Due to the fact much of today's data can be represented as graphs, there has been a demand for generalizing neural network models for graph data. One recent direction that has shown fruitful results, and …