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📐 Results for the Ranking Metrics submission @ GLB 2022
A comparison of Knowledge Graph Embedding methods.
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 place for one-off experiments with PyKEEN that can be re-run anytime
Combining Query Rewriting (PerfectRef) and Knowledge Graph Embeddings with Complex Query Answering
PyKEEN benchmarks with airspeed velocity served at https://pykeen.github.io/asv-benchmark/
🪑 Benchmark the bloom filterer at https://pykeen.github.io/bloom-filterer-benchmark/
🪑 Benchmark collation of negative samples inside the DataLoader
🪑 Benchmark negative samplers' false negative rate
🌐 The website for PyKEEN and the KEEN universe at https://pykeen.github.io
Keywords: PyKEEN / Inductive Reasoning / Deductive Reasoning