🤖 A Python library for learning and evaluating knowledge graph embeddings

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

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

SimplE Embedding for Link Prediction in Knowledge Graphs

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

STransE: a novel embedding model of entities and relationships in knowledge bases (NAACL 2016)

QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings (TheWebConf WWW 2022) (Pytorch)

Paper list for knowledge hypergraph

HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion

Some papers on knowledge graph embedding

🌮 Table-based KB Completer

Python implementation of "Data-dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion [Manabe+. 2018]"

Source code & appendices accompanying the AAAI2022 paper "Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias"

Knowledge Base Completion for Long-Tail Entities

Meta-learning in Knowledge Base completion

Code for project on reasoning over multiple paths

Implementation of a learning and fragment-based rule inference engine -- M. Svatoš, S. Schockaert, J. Davis, and O. Kuželka: STRiKE: Rule-driven relational learning using stratified k-entailment, ECAI'20