relational-learning

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

TypeDB-ML is the Machine Learning integrations library for TypeDB

RelBench: Relational Deep Learning Benchmark

PyNeuraLogic lets you use Python to create Differentiable Logic Programs

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

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

SimplE Embedding for Link Prediction in Knowledge Graphs

Deep relational learning through differentiable logic programming.

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

Open and Reproducible Benchmarking for Relational Learning

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.

ReDeLEx is a Python framework for developing and evaluating RDL models on relational databases via RelBench and CTU datasets.

Showcase notebooks for getML

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

Relational Features for Planning

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

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