TypeDB-ML is the Machine Learning integrations library for TypeDB

[WWWJ 2024] LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

[Tool] For Knowledge Graph Representation Learning

Implementations of Embedding-based methods for Knowledge Base Completion tasks

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

[Paper][AAAI 2025] (MyGO)Tokenization, Fusion, and Augmentation: Towards Fine-grained Multi-modal Entity Representation

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

[Paper][ACM MM 2024] Making Large Language Models Perform Better in Knowledge Graph Completion

Implementation of TransE model in PyTorch.

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

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

SimplE Embedding for Link Prediction in Knowledge Graphs

[Neurocomputing 2023] Relational Graph Transformer for Knowledge Graph Representation

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

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

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

Knowledge Base Question Answering using memory networks

Embedding Projection for Knowledge Graph Completion

Graph Neural Networks for Knowledge Graph Link Prediction (WSDM 2022) (Pytorch)