TensorFlow implementation of TransE and its extended models for Knowledge Representation Learning
-
Updated
Aug 24, 2018 - Python
TensorFlow implementation of TransE and its extended models for Knowledge Representation Learning
Reproduceing the models of Knowledge Representation Learning (KRL), such as TransE, TransH etc.
A simple implement of TransE, the ML algorithm published in 2013
A TensorFlow-based implementation of knowledge graph embedding models.
Tongji Univ. xLab Knowledge Reasoning 2019
TransE implementation in Spark (pyspark)
ARGA,ARGVA,AttentiveFP,Captum,ComplEx,CorrectAndSmooth,DeepGCNLayer,DeepGraphInfomax,DimeNet,DimeNetPlusPlus,DistMult,EdgeCNN,GAE,GAT,GATv2,GCN,GITMol,GLEM,GIN,GNNFF,GraphSAGE,GraphUNet,GRetriever,HeteroJumpingKnowledge,InnerProductDecoder,JumpingKnowledge,KGEModel,LabelPropagation,LightGCN,LINKX,MetaLayer,MetaPath2Vec,MLP,MoleculeGPT,Node2Vec,
Add a description, image, and links to the transe topic page so that developers can more easily learn about it.
To associate your repository with the transe topic, visit your repo's landing page and select "manage topics."