knowledge-graph-embedding-models

Code to accompany the "Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery" manuscript (Artificial Intelligence in the Life Sciences, 2022)

Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction

Quantification of graph structure influence on link prediction and pre-hoc KGEM hyperparameter selection based on Structural Alignment

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/

PyTorch implementation and reproduction of TransE (Bordes et al., 2013) on FB15k