Papers by Patrick Betz

1 papers
LibKGE - A knowledge graph embedding library for reproducible research (2020.emnlp-demos)

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Challenge: Knowledge graph embedding models are trained to predict false triples and high scores for true triples.
Approach: LibKGE is an open-source PyTorch-based library for training, hyperparameter optimization, and evaluation of knowledge graph embedding models for link prediction.
Outcome: LibKGE provides implementations of common knowledge graph embedding models and training methods, and new ones can be easily added.

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