DeepGraphLearning/KnowledgeGraphEmbedding

Health v2 · maintenance only

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Adoption not part of the score

1381 stars · 272 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch toolkit implementing the RotatE knowledge graph embedding model along with TransE, ComplEx, DistMult, and pRotatE. It trains and evaluates KGE models on standard benchmarks like FB15k-237 and WN18RR with self-adversarial negative sampling.

Use cases

• train knowledge graph embeddings with pytorch
• reproduce RotatE ICLR 2019 paper results
• run link prediction on FB15k-237 and WN18RR
• compare TransE ComplEx DistMult RotatE models
• evaluate knowledge graph completion with MRR and Hits@k
• learn how self-adversarial negative sampling works

When to choose

• you need state-of-the-art KGE baselines on standard benchmarks
• you want to reproduce or extend the RotatE paper
• you need fast single-GPU training of knowledge graph embeddings

When to avoid

• you need production serving or an embedding API
• you want multi-GPU or very large-scale training (use GraphVite instead)
• you need actively maintained code with recent dependency updates

Facets

library · maturity maintenance

machine-learning deep-learning rag machine-learning deep-learning artificial-intelligence databases python cross-platform knowledge-graph-embedding pytorch rotate transe complex distmult link-prediction negative-sampling research-code gpu linux

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markdown · JSON · MCP: product_card(name="DeepGraphLearning/KnowledgeGraphEmbedding")