Knowledge Graph Embeddings Edit Task
Graphs • Triple Classification
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Greatest papers with code
Fast Linear Model for Knowledge Graph Embeddings
This paper shows that a simple baseline based on a Bag-of-Words (BoW) representation learns surprisingly good knowledge graph embeddings.
KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPH EMBEDDINGS QUESTION ANSWERING
Low-Dimensional Hyperbolic Knowledge Graph Embeddings
ACL 2020
• tensorflow/neural-structured-learning
• 
However, existing hyperbolic embedding methods do not account for the rich logical patterns in KGs.
Ranked #2 on
Link Prediction
on YAGO3-10
Convolutional 2D Knowledge Graph Embeddings
In this work, we introduce ConvE, a multi-layer convolutional network model for link prediction, and report state-of-the-art results for several established datasets.
Ranked #1 on
Link Prediction
on WN18
DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning
We study the problem of learning to reason in large scale knowledge graphs (KGs).
Ranked #1 on
Link Prediction
on NELL-995
(Mean AP metric)
KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS
Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs
ACL 2019
• deepakn97/relationPrediction
• 
The recent proliferation of knowledge graphs (KGs) coupled with incomplete or partial information, in the form of missing relations (links) between entities, has fueled a lot of research on knowledge base completion (also known as relation prediction).
Ranked #1 on
Knowledge Graph Completion
on FB15k-237
(MRR metric)
KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDINGS LINK PREDICTION
You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings
ICLR 2020
• uma-pi1/kge
•
A vast number of KGE techniques for multi-relational link prediction have been proposed in the recent literature, often with state-of-the-art performance.
HYPERPARAMETER OPTIMIZATION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS LINK PREDICTION
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
• pykeen/pykeen
•
Recently, knowledge graph embeddings (KGEs) received significant attention, and several software libraries have been developed for training and evaluating KGEs.
Ranked #1 on
Link Prediction
on WN18
(training time (s) metric)
KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS LINK PREDICTION
KBGAN: Adversarial Learning for Knowledge Graph Embeddings
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.
Ranked #11 on
Link Prediction
on WN18
KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
A visual-relational knowledge graph (KG) is a multi-relational graph whose entities are associated with images.
IMAGE RETRIEVAL KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS ZERO-SHOT LEARNING
Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings
ACL 2017
• stanfordnlp/cocoa
•
To model both structured knowledge and unstructured language, we propose a neural model with dynamic knowledge graph embeddings that evolve as the dialogue progresses.