In this paper, we propose GraphVite, a high-performance CPU-GPU hybrid system for training node embeddings, by co-optimizing the algorithm and the system.
SOTA for Node Classification on YouTube
We study the problem of learning representations of entities and relations in knowledge graphs for predicting missing links.
#4 best model for Link Prediction on WN18
This framework is independent of the concrete form of generator and discriminator, and therefore can utilize a wide variety of knowledge graph embedding models as its building blocks.
Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems.
Python library for knowledge graph embedding and representation learning.
A visual-relational knowledge graph (KG) is a multi-relational graph whose entities are associated with images.