Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org
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Updated
Nov 22, 2024 - Python
Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org
TypeDB-ML is the Machine Learning integrations library for TypeDB
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
SimplE Embedding for Link Prediction in Knowledge Graphs
[ICLR 2022] Graph-Relational Domain Adaptation
☕ A Python library for gradient-boosted statistical relational models / learning probabilistic relational programs.
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)
[Accepted by TNNLS] Source Code for Relational Redundancy-Free Graph Clustering
Python package for fetching and using srlearn-compatible relational datasets.
🐍🚧 Experimental tool for SRL learning in Python. For something more stable, see: https://github.com/srlearn/srlearn
[COLM'25] PvGaLM is the first privacy-preserving relational learning pipeline that is compatible with DP-SGD.
The source code for "Zero-Shot Relational Learning for Multimodal Knowlege Graphs", In the Proceedings of the 2024 IEEE International Conference on Big Data
Project repository for MA6040: Fuzzy Logic Connectives: Theory and Applications offered in Spring 2019
A code base for Automated Relational Feature Engineering
Distributed Non Negative RESCAL decomposition with estimation of latent features
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.
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