Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

TypeDB-ML is the Machine Learning integrations library for TypeDB

The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification"

PyNeuraLogic lets you use Python to create Differentiable Logic Programs

SimplE Embedding for Link Prediction in Knowledge Graphs

Deep relational learning through differentiable logic programming.

Fast, high-quality forecasts on relational and multivariate time-series data powered by new feature learning algorithms and automated ML.

Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)

A largely incomplete but hopefully useful list of links to datasets for relational learning and inductive logic programming. No guarantees on availability.

[ICLR 2022] Graph-Relational Domain Adaptation

☕ A Python library for gradient-boosted statistical relational models / learning probabilistic relational programs.

RelNN is a novel first-order deep neural model for relational learning.

Machine learning on knowledge graphs for context-aware security monitoring (data and model)

Showcase notebooks for getML

Code and data to the publication "SpikE: spike-based embeddings for multi-relational graph data".

Official implementation of "Relational Proxies: Emergent Relationships as Fine-Grained Discriminators", NeurIPS 2022.

PyTorch implementation of the paper "NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning" (AAAI'24)

The source code repository for the FactorBase system

[Accepted by TNNLS] Source Code for Relational Redundancy-Free Graph Clustering

Graph Learning for Planning [AAAI-24, ICAPS-24, NeurIPS-24]