A Generalization of Transformer Networks to Graphs
Source code for the paper “A Generalization of Transformer Networks to Graphs” by Vijay Prakash Dwivedi and Xavier Bresson, at AAAI’21 Workshop on Deep Learning on Graphs: Methods and Applications (DLG-AAAI’21). We propose a generalization of transformer neural network architecture for arbitrary graphs: Graph Transformer. Compared to the Standard Transformer, the highlights of the presented architecture are: The attention mechanism is a function of neighborhood connectivity for each node in the graph. The position encoding is represented by Laplacian eigenvectors, […]
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