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Graph Neural Networks for Knowledge Graphs | by Michael Shapiro MD MSc | Towards AI

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Making AI accessible to 100K+ learners. Find the most practical, hands-on and comprehensive AI Engineering and AI for Work certifications at academy.towardsai.net - we have pathways for any experience level. Monthly cohorts still open — use COHORT10 for 10% off! Follow publication You're reading for free via Michael Shapiro MD MSc's Friend Link. Become a member to access the best of Medium. Member-only story 107 2 Listen Share Surprisingly, there aren’t many good resources on how to obtain embeddings for nodes in a Knowledge Graph. The challenge lies in the unique nature of KGs in the context of graph learning — they’re large, heterogeneous graphs with multiple edge types and no node features. An abomination, if you ask anyone working in graph learning. (If you’re not a Medium Member, read it for free here) In this tutorial, I’ll walk you through the detailed framework I built to train a GNN for graph embeddings. I’ll be using PyTorch and PyTorch Geometric — arguably the best tools for

Member-only story Knowledge Graph Embedding Graph Neural Networks Graph Neural Networks for Knowledge Graphs A Practical Guide to Data Preparation and Training Graph Neural Networks on Knowledge Graphs Michael Shapiro MD MSc 13 min read · Aug 4, 2025 -- 2 Listen Share Press enter or click to view image in full size License: Generated by the author using ChatGPT Introduction Surprisingly, there aren’t many good resources on how to obtain embeddings for nodes in a Knowledge Graph. The challenge lies in the unique nature of KGs in the context of graph learning — they’re large, heterogeneous graph

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