Ruicheng Ming

Knowledge Graph Embedding with Atrous Convolution and Residual Learning

Knowledge graph embedding is an important task and it will benefit lots of downstream applications. Currently, deep neural networks based methods achieve state-of-the-art performance. However, most of these existing methods are very complex and need much time for training and inference. To address t…