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

Grakn Knowledge Graph Library (ML R&D)

SimplE Embedding for Link Prediction in Knowledge Graphs

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

☕ A Python library for gradient-boosted statistical relational models.

Deep relational learning through differentiable logic programming.

The source code repository for the FactorBase system

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

⚡ SRLBoost: BoostSRL but half the size and twice the speed. Refactor for srlearn's core.

Project repository for MA6040: Fuzzy Logic Connectives: Theory and Applications offered in Spring 2019

Lossless Compression of Structured Convolutional Models via Lifting

🐍🚧 Experimental tool for SRL learning in Python. For something more stable, see: https://github.com/hayesall/srlearn

Beyond Graph Neural Networks with Lifted Relational Neural Networks

Computes contingency tables for relational databases, i.e. counts across tables

Implementation of the framework in the paper: Waegeman, W., Pahikkala, T., Airola, A., Salakoski, T., Stock, M., & De Baets, B. (2012). A kernel-based framework for learning graded relations from data. IEEE Transactions on Fuzzy Systems, 20(6), 1090-1101.