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Implementation of Poincaré embeddings in PyTorch for learning hierarchical representations in hyperbolic space.

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PoincareEmbeddings

My implementation of the paper Poincaré Embeddings for Learning Hierarchical Representations on the dataset HyperLex: A Large Scale Evaluation of Graded Lexical Entailment

Visualisation of the embeddings created on the hyperbolic space

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Citation

@misc{nickel2017poincareembeddingslearninghierarchical,
      title={Poincar\'e Embeddings for Learning Hierarchical Representations}, 
      author={Maximilian Nickel and Douwe Kiela},
      year={2017},
      eprint={1705.08039},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/1705.08039}, 
}
@article{vulic-etal-2017-hyperlex,
    title = "{H}yper{L}ex: A Large-Scale Evaluation of Graded Lexical Entailment",
    author = "Vuli{\'c}, Ivan  and
      Gerz, Daniela  and
      Kiela, Douwe  and
      Hill, Felix  and
      Korhonen, Anna",
    journal = "Computational Linguistics",
    volume = "43",
    number = "4",
    month = dec,
    year = "2017",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://aclanthology.org/J17-4004",
    doi = "10.1162/COLI_a_00301",
    pages = "781--835",
}

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Implementation of Poincaré embeddings in PyTorch for learning hierarchical representations in hyperbolic space.

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