A collection of research on knowledge graphs

Dynamic (Temporal) Knowledge Graph Completion (Reasoning)

TypeDB-ML is the Machine Learning integrations library for TypeDB

[Tool] For Knowledge Graph Representation Learning

Implementations of Embedding-based methods for Knowledge Base Completion tasks

Datasets for Knowledge Graph Completion with textual information about the entities

The code of paper Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang. AAAI 2020.

Embedding Projection for Knowledge Graph Completion

A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network (NAACL 2018) (Pytorch and Tensorflow)

ACL 2022, SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models

SimplE Embedding for Link Prediction in Knowledge Graphs

ConMask model described in paper Open-world Knowledge Graph Completion.

LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

Implementation of TransE model in PyTorch.

A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization (NAACL 2019)

Knowledge Base Question Answering using memory networks

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

ACL 2020: A Re-evaluation of Knowledge Graph Completion Methods

AAAI 2020 - InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions