Link Prediction On Wn18

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Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

						Paper Title
Inverse Model	0.953	0.964	0.964	740	0.963	Convolutional 2D Knowledge Graph Embeddings
LineaRE	0.947	0.961	0.955	170	0.952	LineaRE: Simple but Powerful Knowledge Graph Embedding for Link Prediction
QuatDE	0.944	0.961	0.954	120	0.95	QuatDE: Dynamic Quaternion Embedding for Knowledge Graph Completion
AutoKGE	-	0.961	-	-	0.952	AutoSF: Searching Scoring Functions for Knowledge Graph Embedding
MEI (small)	0.946	0.960	0.953	-	0.951	Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion
ComplEx-N3 (reciprocal)	-	0.96	-	-	-	Canonical Tensor Decomposition for Knowledge Base Completion
QuatE	0.945	0.959	0.954	162	0.95	Quaternion Knowledge Graph Embeddings
RotatE	0.944	0.959	0.952	309	0.949	RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
DensE	0.945	0.959	0.954	285	0.950	DensE: An Enhanced Non-commutative Representation for Knowledge Graph Embedding with Adaptive Semantic Hierarchy
ConvR	0.947	0.958	0.955	-	0.951	Adaptive Convolution for Multi-Relational Learning
HypER	0.947	0.958	0.955	-	0.951	Hypernetwork Knowledge Graph Embeddings
TuckER	0.949	0.958	0.955	-	0.953	TuckER: Tensor Factorization for Knowledge Graph Completion
pRotatE	0.942	0.957	0.950	254	0.947	RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
MEI-BTD	0.946	0.957	0.952	-	0.950	Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion
OPTransE	-	0.957	-	199	-	Representation Learning with Ordered Relation Paths for Knowledge Graph Completion
Quaternion	0.931	0.956	0.950	-	0.941	Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective
ConvE	0.935	0.956	0.946	374	0.943	Convolutional 2D Knowledge Graph Embeddings
MDE	-	0.956	-	118	0.871	MDE: Multiple Distance Embeddings for Link Prediction in Knowledge Graphs
SimplE	0.944	0.954	0.950	412	0.948	GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
HHolE	.931	.951	.945	183	.939	Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations

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Link Prediction On Wn18

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