Knowledge Graphs

937 papers with code • 3 benchmarks • 41 datasets

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Libraries

Use these libraries to find Knowledge Graphs models and implementations
4 papers
2,072
3 papers
1,927
3 papers
37
2 papers
585

Most implemented papers

Embedding Logical Queries on Knowledge Graphs

williamleif/graphqembed NeurIPS 2018

Learning low-dimensional embeddings of knowledge graphs is a powerful approach used to predict unobserved or missing edges between entities.

TuckER: Tensor Factorization for Knowledge Graph Completion

ibalazevic/TuckER IJCNLP 2019

Knowledge graphs are structured representations of real world facts.

MMKG: Multi-Modal Knowledge Graphs

nle-ml/mmkb 13 Mar 2019

We present MMKG, a collection of three knowledge graphs that contain both numerical features and (links to) images for all entities as well as entity alignments between pairs of KGs.

Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems

hwwang55/KGNN-LS 11 May 2019

Here we propose Knowledge-aware Graph Neural Networks with Label Smoothness regularization (KGNN-LS) to provide better recommendations.

Holographic Embeddings of Knowledge Graphs

Accenture/AmpliGraph 16 Oct 2015

Learning embeddings of entities and relations is an efficient and versatile method to perform machine learning on relational data such as knowledge graphs.

Multi-Relational Embedding for Knowledge Graph Representation and Analysis

tranhungnghiep/AnalyzeKGE PhD Dissertation, The Graduate University for Advanced Studies, SOKENDAI, Japan 2020

The goal of this thesis is first to study multi-relational embedding on knowledge graphs to propose a new embedding model that explains and improves previous methods, then to study the applications of multi-relational embedding in representation and analysis of knowledge graphs.

Logic Embeddings for Complex Query Answering

francoisluus/KGReasoning 28 Feb 2021

Answering logical queries over incomplete knowledge bases is challenging because: 1) it calls for implicit link prediction, and 2) brute force answering of existential first-order logic queries is exponential in the number of existential variables.

QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering

michiyasunaga/qagnn NAACL 2021

The problem of answering questions using knowledge from pre-trained language models (LMs) and knowledge graphs (KGs) presents two challenges: given a QA context (question and answer choice), methods need to (i) identify relevant knowledge from large KGs, and (ii) perform joint reasoning over the QA context and KG.

NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs

migalkin/NodePiece ICLR 2022

To this end, we propose NodePiece, an anchor-based approach to learn a fixed-size entity vocabulary.

MEIM: Multi-partition Embedding Interaction Beyond Block Term Format for Efficient and Expressive Link Prediction

tranhungnghiep/meim-kge 30 Sep 2022

Knowledge graph embedding aims to predict the missing relations between entities in knowledge graphs.