Empirical experiments on multiple real-world datasets demonstrate that DrGNN outperforms state-of-the-art deep graph representation baseline algorithms. The ...
cessible under the name “CityPulse Smart City Datasets” on the internet which includes various attributes like vehicle id, latitude, longitude, timestamp ...
The paper proposes the DRGNN, a semi - supervised learning framework. It includes a mask strategy in the graph autoencoder, an initial residual connection in ...
Search by expertise, name or affiliation. DrGNN: Deep Residual Graph Neural Network with Contrastive Learning. Lecheng Zheng, Dongqi Fu, Ross Maciejewski ...
Motivated by this, we propose a novel graph neural network named DrGNN to alleviate the oversmoothing issue from the perspective of addressing dimensional ...