🤖 A Python library for learning and evaluating knowledge graph embeddings
🏅 KG Inductive Link Prediction Challenge (ILPC) 2022
📐 Results for the Ranking Metrics submission @ GLB 2022
A knowledge graph containing 5 million research papers. Uses: compute Erdős numbers, rank influence of cities on research areas, detect whether researchers with the same name are the same person.
A project to predict new repurposed drugs for dengue using a biomedical knowledge graph and graph neural networks.
A comparison of Knowledge Graph Embedding methods.
Explainable AI framework for drug repurposing using biomedical knowledge graphs and counterfactual reasoning.
A place for one-off experiments with PyKEEN that can be re-run anytime
🌐 The website for PyKEEN and the KEEN universe at https://pykeen.github.io
Combining Query Rewriting (PerfectRef) and Knowledge Graph Embeddings with Complex Query Answering
Knowledge-graph construction, Wikidata alignment, OWL reasoning, PyKEEN embeddings and NL-to-SPARQL RAG over Wikipedia data. ESILV Web Datamining & Semantics project.
Keywords: PyKEEN / Inductive Reasoning / Deductive Reasoning
Special Topics II Term Project — Knowledge graph modeling and graph ML on a Neo4j movie recommendation graph — exploratory graph analysis, topological feature engineering (ReFeX), link prediction, node classification, and KG completion with TransE/DistMult embeddings.
PyKEEN benchmarks with airspeed velocity served at https://pykeen.github.io/asv-benchmark/
Hybrid fact checking over knowledge graphs combining graph features, KG embeddings (RotatE, ComplEx), and supervised learning.
🪑 Benchmark the bloom filterer at https://pykeen.github.io/bloom-filterer-benchmark/
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